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Aims/hypothesis: The diagnosis of type 2 diabetes is increasing in young people worldwide. This study evaluated the frequency and clinical characteristics of young people presenting with type 2 diabetes from the multinational SWEET e.V Registry 2012-2021, including the first years of the COVID-19 pandemic., Methods: This is a longitudinal observational study based on the SWEET Registry, which collects demographic and clinical data on children and adolescents with diabetes from centres worldwide, with the diagnosis and classification of diabetes provided locally by each centre according to International Society for Paediatric and Adolescent Diabetes definitions. By July 2022, the SWEET Registry included 96,931 individuals from 130 centres with a total of 1,154,555 visits. Data were analysed by region: Europe (EU), Australia and New Zealand (AU/NZ), South America (SA), North America (NA) and Asia/Middle East and Africa (AS/AF). Trends in proportions for the two-year periods, calculated as cases with type 2 diabetes diagnoses over all cases with diabetes diagnoses, were estimated using logistic regression models adjusted for age at onset and sex., Results: Overall, there were 2819 of 58,170 new cases (4.8%) with type 2 diabetes: 614 in EU, 293 in AU/NZ, 79 in SA, 1211 in NA and 622 in AS/AF. The proportion of type 2 diabetes increased from 3.2% to 6.0% from 2012/2013 to 2020/2021, a relative rate of increase of 9% per two-year period (95% CI 5.9, 12.3; p<0.001). In the two-year period of the COVID-19 pandemic, type 2 diabetes continued to follow the observed trend, with a proportion of 6.0% in 2020-2021 compared with 5.4% in 2018-2019. High variability in the proportion of type 2 diabetes was observed across regions, with the lowest values observed in EU and the highest in NA. A significant increase in the proportion of type 2 diabetes was observed in EU, AU/NZ and NA. The median HbA 1c was not uniform and was highest in AS/AF (85 mmol/mol [9.9%]; IQR 55-111 [7.2-12.3%]) and lowest in EU (63 mmol/mol [7.9%]; IQR 48-99 [6.5-11.2%]), and the difference between EU and NA (median value 73 mmol/mol [8.8%]; IQR 50-105 [6.7-11.8%]) was statistically significant (p=0.047). There was also a difference in BMI SD score by region: the lowest median BMI SD score was 2.2 (IQR 1.4-2.7) in AS/AF and the highest was 3.1 (IQR 2.5-3.6) in AU/NZ., Conclusions/interpretation: The multinational SWEET data from the years 2012 to 2021 inclusive support recent findings of a worldwide increase in type 2 diabetes in young people, albeit with regional differences. This increase highlights the need for ongoing preventive measures and available advanced treatment modalities worldwide., (© 2024. The Author(s).)

Aims: Diabetic foot ulcer (DFU) is a leading cause of lower limb amputations in people with diabetes. This study was aimed to retrospectively analyze factors affecting DFU using real-world data from a large, prospective central-European diabetes registry (DPV [Diabetes-Patienten-Verlaufsdokumentation])., Materials and Methods: We matched adults with type 1 (T1D) or type 2 diabetes (T2D) and DFU to controls without DFU by diabetes type, age, sex, diabetes duration, and treatment year to compare possible risk factors. Cox regression was used to calculate hazard ratios for amputation among those with DFU., Results: In our cohort (N = 63 464), male sex, taller height, and diabetes complications such as neuropathy, peripheral artery disease, nephropathy, and retinopathy were associated with DFU (all p < .001). Glycated hemoglobin (HbA1c) was related to DFU only in T1D (mean with 95% confidence interval [CI]: 7.8 [6.9-9.0] % vs 7.5 [6.8-8.5] %, p < .001). High triglycerides and worse low-density lipoprotein/high-density lipoprotein ratio were also associated with DFU in T1D, whereas smoking (14.7% vs 13.1%) and alcohol abuse (6.4% vs 3.8%, both p < .001) were associated with DFU in T2D. Male sex, higher Wagner grades, and high HbA1c in both diabetes types and insulin use in T2D were associated with increased hazard ratios for amputations., Conclusions: Sex, body height, and diabetes complications were associated DFU risk in adults with T1D and T2D. Improvement in glycemic control and lipid levels in T1D and reduction of smoking and drinking in T2D may be appropriate interventions to reduce the risk for DFU or amputations., (© 2024 The Authors. Journal of Diabetes published by Ruijin Hospital, Shanghai Jiaotong University School of Medicine and John Wiley & Sons Australia, Ltd.)

Context: Treatment of children with classical congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency is challenging. Linear growth and adult height are compromised according to recent publications. However, most of these data were obtained in the era before CAH newborn screening., Design: Body height of patients with classical CAH diagnosed before and after the establishment of newborn screening were analyzed retrospectively., Patients and Methods: We identified 600 patients with classical CAH (227 male) with data on near-adult height (NAH), target height (TH), and information on newborn screening from the electronic German CAH registry (German Society for Paediatric Endocrinology and Diabetology). Newborn screening was performed in 101 (16.8%) patients. All patients received hydrocortisone with or without fludrocortisone.To assess the effects of newborn screening, a linear regression model adjusted/stratified for sex and phenotype was used (SAS 9.4)., Results: TH corrected NAH (mean; 95% confidence interval) was closer to 0 in patients with CAH and newborn screening [-0.25 standard deviation score (SDS); -0.44 to -0.06] than in patients without newborn screening (-0.44 SDS; -0.52 to -0.36) (P = .069). Screening had no effect on NAH in female patients. In male patients, NAH was significantly better (P = .033) with screening than without screening. After stratifying for CAH phenotype, screening did not affect the NAH of patients with salt-wasting CAH. Patients with simple-virilizing CAH had a significantly better cNAH (P = .034) with screening (0.15 SDS; -0.28-0.59) than without screening (-0.35 SDS; -0.52 to -0.18)., Conclusions: Our data suggest that newborn screening might be associated with improved NAH in male CAH patients and in patients with simple-virilizing CAH., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Endocrine Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: Diabetes technology improves glycemic control and quality of life for many people with type 1 diabetes (T1D). However, inequalities in access to diabetes technology exist in many countries. In Germany, disparities in technology use have been described in pediatric T1D, but no data for adults are available so far. We therefore aimed to analyze whether demographic factors and area deprivation are associated with technology use in a representative population of adults with T1D., Materials and Methods: In adults with T1D from the German prospective diabetes follow-up registry (DPV), we analyzed the use of continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), and sensor augmented pump therapy (SAP, with and without automated insulin delivery) in 2019-2021 by age group, gender, migration background, and area deprivation using multiple adjusted regression models. Area deprivation, defined as a relative lack of area-based resources, was measured by quintiles of the German index of Multiple Deprivation (GIMD 2015, from Q1, least deprived, to Q5, most deprived districts)., Results: Among 13,351 adults with T1D, the use of technology decreased significantly with older age: CSII use fell from 56.1% in the 18-<25-year age group to 3.1% in the ≥80-year age group, CGM use from 75.3% to 28.2%, and SAP use from 45.1% to 1.5% (all p for trend <0.001). The use of technology was also significantly higher in women than in men (CSII: 39.2% vs. 27.6%; CGM: 61.9% vs. 58.0%; SAP: 28.7% vs. 19.6%, all p <0.001), and in individuals without migration background than in those with migration background (CSII: 38.8% vs. 27.6%; CGM: 71.1% vs. 61.4%; SAP: 30.5% vs. 21.3%, all p <0.001). Associations with area deprivation were not linear: the use of each technology decreased only from Q2 to Q4., Discussion: Our real-world data provide evidence that higher age, male gender, and migration background are currently associated with lower use of diabetes technology in adults with T1D in Germany. Associations with area deprivation are more complex, probably due to correlations with other factors, like the higher proportion of migrants in less deprived areas or the federal structure of the German health care system., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Auzanneau, Eckert, Meyhöfer, Heni, Gillessen, Schwettmann, Jehle, Hummel and Holl.)

Objective: To evaluate common surgical procedures and admission causes in inpatient cases with diabetes in Germany between 2015 and 2019 and compare them to inpatient cases without diabetes., Methods: Based on the German diagnosis-related groups (G-DRG) statistics, regression models stratified by age groups and gender were used to calculate hospital admissions/100,000 individuals, hospital days as well as the proportion of complications and mortality in inpatient cases ≥ 40 years with or without a documented diagnosis of diabetes (type 1 or type 2)., Results: A total of 14,222,326 (21%) of all inpatient cases aged ≥ 40 years had a diagnosis of diabetes. More middle-aged females with vs. without diabetes/100,000 individuals [95% CI] were observed, most pronounced in cases aged 40-< 50 years with myocardial infarction (305 [293-319] vs. 36 [36-37], p < 0.001). Higher proportions of complications and longer hospital stays were found for all procedures and morbidities in cases with diabetes., Conclusion: Earlier hospitalizations, longer hospital stays and more complications in inpatient cases with diabetes together with the predicted future increase in diabetes prevalence depict huge challenges for the German healthcare system. There is an urgent need for developing strategies to adequately care for patients with diabetes in hospital., (© 2023. The Author(s).)

Background: Trends over time and possible socio-spatial inequalities in the incidence and care of type 1 diabetes mellitus (T1D) in children and adolescents are important parameters for the planning of target-specific treatment structures., Methodology: The incidence and prevalence of type 1 diabetes, diabetic ketoacidosis and severe hypoglycaemia as well as the HbA1c value are presented for under 18-year-olds based on data from the nationwide Diabetes Prospective Follow-up Registry (DPV) and the diabetes registry of North Rhine-Westphalia. Indicators were mapped by sex over time between 2014 and 2020, and stratified by sex, age and regional socioeconomic deprivation for 2020., Results: In 2020, the incidence was 29.2 per 100,000 person-years and the prevalence was 235.5 per 100,000 persons, with the figures being higher in boys than in girls in either case. The median HbA1c value was 7.5%. Ketoacidosis manifested in 3.4% of treated children and adolescents, significantly more often in regions with very high (4.5%) deprivation than in regions with very low deprivation (2.4%). The proportion of severe hypoglycaemia cases was 3.0%. Between 2014 and 2020, the incidence, prevalence and HbA1c levels changed little, while the proportions of ketoacidosis and severe hypoglycaemia decreased., Conclusions: The decrease in acute complications indicates that type 1 diabetes care has improved. Similar to previous studies, the results suggest an inequality in care by regional socioeconomic situation., (© Robert Koch Institute. All rights reserved unless explicitly granted.)

Background: Fasting indices of glucose-insulin-metabolism are an easy and affordable tool to assess insulin resistance. We aimed to establish reference ranges for fasting insulin indices that reflect age-dependent variation over the entire life span and subsequently test their clinical application regarding the prediction of glycemic deterioration in children., Methods: We calculated age- and puberty-dependent reference values for HOMA-IR, HOMA2-IR, HOMA-β, McAuley index, fasting insulin, and fasting glucose from 6994 observations of 5512 non-obese healthy subjects aged 5-80 years. Applying those references, we determined the prevalence of insulin resistance among 2538 subjects with obesity. Furthermore, we investigated the intraindividual stability and the predictive values for future dysglycemia of these fasting indices in 516 children and adolescents with obesity up to 19 years of follow-up. We validated the results in three independent cohorts., Findings: There was a strong age-dependent variation of all indices throughout the life span, including prolonged recovery of pubertal insulin resistance and a subsequent continuous increase throughout adulthood. Already from age 5 years onwards, >40% of children with obesity presented with elevated parameters of insulin resistance. Applying newly developed reference ranges, insulin resistance among children with obesity doubled the risk for future glycemic deterioration (HOMA-IR HR 1.88 (95% CI 1.1-3.21)), fasting insulin HR 1.89 (95% CI 1.11-3.23). In contrast, fasting glucose alone was not predictive for emerging dysglycemia in children with obesity (HR 1.03 (95% CI 0.62-1.71)). The new insulin-based thresholds were superior to fasting glucose and HbA1c in detecting children eventually manifesting with dysglycemia in prospective analyses., Interpretation: The variation of fasting glucose-insulin-metabolism across the life span necessitates age-specific reference ranges. The improved prediction of future glycemic deterioration by indices based on fasting insulin beyond simple glucose measures alone could help to stratify risk characteristics of children with obesity in order to guide patient-tailored prevention and intervention approaches., Funding: German Research Foundation (DFG)-through SFB 1052, project number 209933838, subproject C5; Federal Ministry of Education and Research, Germany; European Union-European Regional Development Fund; Free State of Saxony. The German Diabetes Association, the CarbHealth consortium (01EA1908B). EU-IMI2-Consortium SOPHIA (grant agreement No 875534), German Center for Diabetes Research (DZD), grant number 82DZD14E03., Competing Interests: MB received honoraria and consulting fees from Amgen, AstraZeneca, Bayer, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis and Sanofi and is part of the advisory board from Boehringer-Ingelheim. All other authors have no conflicts of interest relevant to this article to disclose., (© 2023 The Author(s).)

Objective: To analyze the proportion of diabetes among all hospitalized cases in Germany between 2015 and 2020., Methods: Using the nationwide Diagnosis-Related-Groups statistics, we identified among all inpatient cases aged ≥ 20 years all types of diabetes in the main or secondary diagnoses based on ICD-10 codes, as well all COVID-19 diagnoses for 2020., Results: From 2015 to 2019, the proportion of cases with diabetes among all hospitalizations increased from 18.3% (3.01 of 16.45 million) to 18.5% (3.07 of 16.64 million). Although the total number of hospitalizations decreased in 2020, the proportion of cases with diabetes increased to 18.8% (2.73 of 14.50 million). The proportion of COVID-19 diagnosis was higher in cases with diabetes than in those without in all sex and age subgroups. The relative risk (RR) for a COVID-19 diagnosis in cases with vs without diabetes was highest in age group 40-49 years (RR in females: 1.51; in males: 1.41)., Conclusions: The prevalence of diabetes in the hospital is twice as high as the prevalence in the general population and has increased further with the COVID-19 pandemic, underscoring the increased morbidity in this high-risk patient group. This study provides essential information that should help to better estimate the need for diabetological expertise in inpatient care settings.

Mental comorbidities in patients with type 1 diabetes mellitus (T1D) are common, and can have a negative impact on acute blood glucose levels and long-term metabolic control. Information on the association of T1D and comorbid posttraumatic stress disorder (PTSD) with diabetes-related outcomes is limited. The aim was to examine the associations between a clinical diagnosis of PTSD and diabetes-related outcomes in patients with T1D. Patients with T1D and comorbid documented PTSD from the DPV database (n = 179) were compared to a group with T1D without PTSD (n = 895), and compared to a group with T1D without comorbid mental disorder (n = 895) by matching demographics (age, gender, duration of diabetes, therapy and migration background) 1:5. Clinical diabetes-related outcomes {body mass index (BMI), hemoglobin A1c (hbA1c), daily insulin dose, diabetic ketoacidosis (DKA), hypoglycemia, number of hospital admissions, number of hospital days} were analyzed, stratified by age groups (≤ 25 years vs. > 25 years). Patients with comorbid PTSD aged ≤ 25 years compared with patients without PTSD or patients without mental disorders had significantly higher HbA1c (8.71 vs. 8.30 or 8.24%), higher number of hospital admissions (0.94 vs. 0.44 or 0.32 per year) and higher rates of DKA (0.10 vs. 0.02 or 0.01 events/year). Patients with comorbid PTSD aged ≤ 25 years compared with patients without PTSD had significantly higher BMI (0.85 vs. 0.59) and longer hospital stays (15.89 vs.11.58 days) than patients without PTSD. Patients with PTSD > 25 years compared with patients without PTSD or without any mental comorbidities had significantly fewer hospital admissions (0.49 vs. 0.77 or 0.69), but a longer hospital length of stay (20.35 vs. 11.58 or 1.09 days). We found that PTSD in younger patients with T1D is significantly related to diabetes outcome. In adult patients with T1D, comorbid PTSD is associated with fewer, but longer hospitalizations. Awareness of PTSD in the care of patients with T1D should be raised and psychological intervention should be provided when necessary., (© 2023. The Author(s).)

Background: The diverse stages of the COVID-19 pandemic led to several social circumstances that influenced daily life and health behavior., Purpose: To evaluate changes in cardiovascular risk factors and physical activity among children and young adults with type 1 diabetes (T1D) during the COVID-19 pandemic in Germany compared to previous years., Methods: A total of 32 785 individuals aged 6-21 years at baseline with T1D from the German diabetes patient follow-up (DPV) registry contributed data on 101 484 person-years between 2016 and 2021. The first treatment year of each individual within this period was considered as baseline. Based on trends from 2016 to 2019, we estimated differences in body mass index-SD score (BMI-SDS), blood pressure (BP-SDS), and lipid levels (non-high-density lipoprotein [non-HDL]) between observed and predicted estimates for the years 2020 and 2021 using linear regression analysis standardized for age, diabetes duration, sex, and migratory background. The proportion doing organized sports and smoking cigarettes was analyzed using multivariable logistic regression models., Results: BMI-SDS increased constantly from 2016 to 2021 without a significant increase above expected values for 2020/2021. Systolic BP-SDS (difference observed vs. expected with 95% confidence interval, 2020: 0.10 [0.07-0.14], 2021: 0.17 [0.14-0.20]) and non-HDL (2020: 2.7 [1.3-4.1] mg/dl, 2021: 4.1 [2.7-5.5] mg/dl) were significantly increased (all p < .001) in both pandemic years. The proportion of subjects participating in organized sports was reduced from over 70% in prepandemic years to 35%-65% in diverse stages/waves of the COVID-19 pandemic. The percentage smoking cigarettes did not change., Conclusions: We describe an increase in BP and atherogenic lipid levels coinciding with a reduction in physical activity but no acceleration of the prepandemic increases in BMI-SDS among young people with T1D during the COVID-19 pandemic., (© 2022 The Authors. Journal of Diabetes published by Ruijin Hospital, Shanghai JiaoTong University School of Medicine and John Wiley & Sons Australia, Ltd.)

Background: An increased prevalence of diabetic ketoacidosis at diagnosis of type 1 diabetes in children was observed in various diabetes centres worldwide during the COVID-19 pandemic. We aimed to evaluate trends in the prevalence of diabetic ketoacidosis at diagnosis of paediatric type 1 diabetes before and during the COVID-19 pandemic, and to identify potential predictors of changes in diabetic ketoacidosis prevalence during the pandemic., Methods: For this international multicentre study, we used data from 13 national diabetes registries (Australia, Austria, Czechia, Denmark, Germany, Italy, Luxembourg, New Zealand, Norway, Slovenia, Sweden, USA [Colorado], and Wales). The study population comprised 104 290 children and adolescents aged 6 months to younger than 18 years, who were diagnosed with type 1 diabetes between Jan 1, 2006, and Dec 31, 2021. The observed diabetic ketoacidosis prevalence in 2020 and 2021 was compared to predictions based on trends over the pre-pandemic years 2006-19. Associations between changes in diabetic ketoacidosis prevalence and the severity of the COVID-19 pandemic and containment measures were examined with excess all-cause mortality in the whole population and the Stringency Index from the Oxford COVID-19 Government Response Tracker., Findings: 87 228 children and adolescents were diagnosed with type 1 diabetes between 2006 and 2019, 8209 were diagnosed in 2020, and 8853 were diagnosed in 2021. From 2006 to 2019, diabetic ketoacidosis at diagnosis of type 1 diabetes was present in 23 775 (27·3%) of 87 228 individuals and the mean annual increase in the prevalence of diabetic ketoacidosis in the total cohort from 2006 to 2019 was 1·6% (95% CI 1·3 to 1·9). The adjusted observed prevalence of diabetic ketoacidosis at diagnosis of type 1 diabetes was 39·4% (95% CI 34·0 to 45·6) in 2020 and 38·9% (33·6 to 45·0) in 2021, significantly higher than the predicted prevalence of 32·5% (27·8 to 37·9) for 2020 and 33·0% (28·3 to 38·5) for 2021 (p&lt;0·0001 for both years). The prevalence of diabetic ketoacidosis was associated with the pandemic containment measures, with an estimated risk ratio of 1·037 (95% CI 1·024 to 1·051; p&lt;0·0001) per ten-unit increase in the Stringency Index for 2020 and 1·028 (1·009 to 1·047; p=0·0033) for 2021, but was not significantly associated with excess all-cause mortality., Interpretation: During the COVID-19 pandemic, there was a marked exacerbation of the pre-existing increase in diabetic ketoacidosis prevalence at diagnosis of type 1 diabetes in children. This finding highlights the need for early and timely diagnosis of type 1 diabetes in children and adolescents., Funding: German Federal Ministry for Education and Research, German Robert Koch Institute, German Diabetes Association, German Diabetes Foundation, Slovenian Research Agency, Welsh Government, Central Denmark Region, and Swedish Association of Local Authorities and Regions., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: This study investigated the diagnostic delay and the subsequent quality of care during the Covid-19 pandemic among children with new-onset type 1 diabetes., Methods: We compared the HbA 1c levels of 3111 children at diagnosis of type 1 diabetes and of 2825 children at a median follow-up of 4.7 months (interquartile range, 4.1-5.4) together with their daily insulin requirement during the Covid-19 pandemic with the two previous years via multivariable linear regression, using data from the German Diabetes Registry DPV., Results: During the Covid-19 pandemic, HbA 1c levels were higher at diagnosis of type 1 diabetes (mean estimated difference, 0.33% [95% confidence interval, 0.23-0.43], p < 0.001), but not at follow-up (mean estimated difference, 0.02% [-0.02-0.07]). Children with diabetes onset during the Covid-19 pandemic had a significantly higher daily insulin requirement after initiation of therapy (mean estimated difference, 0.08 U/kg [0.06-0.10], p < 0.001). Both the increase in HbA 1c and daily insulin requirement were evident only after the first wave of the pandemic., Conclusions: This increase in HbA 1c at diagnosis of type 1 diabetes during the Covid-19 pandemic may indicate a delay in seeking medical care due to the pandemic. However, this did not affect short-term glycemic control. The increased insulin requirement at follow-up could suggest a more rapid autoimmune progression during the pandemic., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

Objective: The aim of this study was to investigate the incidence of type 1 diabetes in children and adolescents during the coronavirus disease 2019 (COVID-19) pandemic in Germany compared with previous years., Research Design and Methods: Based on data from the multicenter German Diabetes Prospective Follow-up Registry, we analyzed the incidence of type 1 diabetes per 100,000 patient-years in children and adolescents from 1 January 2020 through 30 June 2021. Using Poisson regression models, expected incidences for 2020/21 were estimated based on the data from 2011 to 2019 and compared with observed incidences in 2020/21 by estimating incidence rate ratios (IRRs) with 95% CIs., Results: From 1 January 2020 to 30 June 2021, 5,162 children and adolescents with new-onset type 1 diabetes in Germany were registered. The observed incidence in 2020/21 was significantly higher than the expected incidence (24.4 [95% CI 23.6-25.2] vs. 21.2 [20.5-21.9]; IRR 1.15 [1.10-1.20]; P < 0.001). IRRs were significantly elevated in June 2020 (IRR 1.43 [1.07-1.90]; P = 0.003), July 2020 (IRR 1.48 [1.12-1.96]; P < 0.001), March 2021 (IRR 1.29 [1.01-1.65]; P = 0.028), and June 2021 (IRR 1.39 [1.04-1.85]; P = 0.010)., Conclusions: A significant increase in the incidence of type 1 diabetes in children was observed during the COVID-19 pandemic, with a delay in the peak incidence of type 1 diabetes by ∼3 months after the peak COVID-19 incidence and also after pandemic containment measures. The underlying causes are yet unknown. However, indirect rather than direct effects of the pandemic are more likely to be the cause., (© 2022 by the American Diabetes Association.)

Aims: To examine the association of frozen shoulder (FS) with demographic and diabetes-related outcomes in individuals with type 1 (T1D) or type 2 (T2D) diabetes aged ≥30 years., Materials and Methods: Multivariable logistic regression models, adjusted for demographics were used to calculate the proportion of FS in association with age, gender, diabetes duration, body mass index (BMI), haemoglobin A1C (HbA1c) and diabetes treatment., Results: The unadjusted percentage of FS was higher in T1D compared to T2D (0.22% vs. 0.06%). In T1D, adjusted regression models revealed higher prevalence of FS in women than men (0.26 [0.20-0.34] % vs. 0.15 [0.11-0.21] %, p =0.010). No significant relationship of age and BMI with FS was found in both diabetes types. Longer diabetes duration was associated with a higher proportion of FS in T1D (p <0.001) and T2D ( p =0.004). In T1D, HbA1c >7% was related to a higher proportion of FS compared to HbA1c ≤7% (0.25 [0.19-0.32] vs. 0.12 [0.08-0.20] %, p =0.007), while an inverse relationship was found in T2D (HbA1c ≤7%: 0.08 [0.07-0.10] vs. HbA1c >7%: 0.05 [0.04-0.06] %, p =0.001)., Conclusions: Different associations of FS with gender and HbA1c were observed for T1D and T2D; however, longer diabetes duration increases the risk for FS independent of diabetes type. Musculoskeletal diseases are still underreported in individuals with diabetes and awareness should be raised for FS as a specific diabetes complication., Competing Interests: The authors declare that they have no conflict of interest., (Thieme. All rights reserved.)

Congenital primary hypothyroidism (CH) and congenital adrenal hyperplasia (CAH) are targeted by the German and Austrian newborn screening. For both diseases, there are registries for quality improvement, based on standardized observational data from long-term patient follow-up, under the auspices of the DGKED study group. By September 2021, the CH registry HypoDOK includes datasets from 23,348 visits of 1,840 patients, and the CAH registry contains datasets from 36,237 visits of 1,976 patients. Here, we report on the recruitment process, patient characteristics, and research contributions from the registries, and underline that the registries are an important tool to improve patient care and outcomes. Registries for rare conditions should thus be considered as an important public health measure and they should be adequately institutionalized and funded., Competing Interests: Competing interests: Authors state no conflict of interest., (© 2022 Hammersen et al., published by De Gruyter.)

Objective: To study diabetic cataract in type 1 diabetes in a large pediatric cohort., Methods: The 92,633 patients aged 0.5-21 years from German/Austrian multicenter diabetes registry (DPV) were analyzed. The 235 patients (0.25%) with diabetic cataract were found, 200 could be categorized: 67 with early cataract (3 months before diabetes onset - 12 months afterwards), 133 with late cataract (>12 months after diabetes onset). Regression models adjusted for age and gender were used to compare clinical parameters at diabetes onset. Regression models for patients with late cataract were implemented for the total documentation period and additionally adjusted for diabetes duration., Results: Rate of cataract development shows a peak at diabetes onset and declines with longer diabetes duration. Patients with cataract showed strong female preponderance. Patients developing early cataract were older at diabetes onset (12.8 years [11.8/13.9] vs. 8.9 [8.9/9.0]; p < 0.001) and showed higher HbA1c than patients without cataract (9.0% [8.55/9.38] vs. 7.6% [7.60/7.61]; p < 0.001). They had lower height-SDS, (-0.22 [-0.48/0.04] vs. 0.25 [0.24/0.26]; p < 0.001), lower weight-SDS (-0.31 [-0.55/-0.08] vs. 0.21 [0.20/0.21]; p < 0.001) and lower BMI-SDS (-0.25 [-0.49/-0.02] vs. 0.12 [0.12/0.13); p = 0.002). Patients with late cataract showed higher HbA1c at diabetes onset (8.35% [8.08/8.62] vs. 8.04% [8.03/8.05]; p = 0.023) and higher mean HbA1c during total documentation period (8.00% [7.62/8.34] vs. 7.62% [7.61/7.63]; p = 0.048)., Conclusions: Our data confirm known demographic and clinical characteristics of patients developing early cataract. Hyperglycemia-induced osmotic damage to lens fibers at diabetes onset might be the main pathomechanism. Long term glycemic control is associated with cataract development., (© 2022 The Authors. Pediatric Diabetes published by John Wiley & Sons Ltd.)

A decade of genetic association studies in multiple organisms suggests that most complex traits are polygenic; that is, they have a genetic architecture determined by numerous loci, each with small effect-size. Thus, determining the degree of polygenicity and its variation across traits, environments and time is crucial to understand the genetic basis of phenotypic variation. We applied multilocus approaches to estimate the degree of polygenicity of fitness-related traits in a long-lived plant (Pinus pinaster Ait., maritime pine) and to analyse this variation across environments and years. We evaluated five categories of fitness-related traits (survival, height, phenology, functional, and biotic-stress response) in a clonal common-garden network planted in contrasted environments (over 20,500 trees). Most of the analysed traits showed evidence of local adaptation based on Q st -F st comparisons. We further observed a remarkably stable degree of polygenicity, averaging 6% (range of 0%-27%), across traits, environments and years. We detected evidence of negative selection, which could explain, at least partially, the high degree of polygenicity. Because polygenic adaptation can occur rapidly, our results suggest that current predictions on the capacity of natural forest tree populations to adapt to new environments should be revised, especially in the current context of climate change., (© 2022 John Wiley & Sons Ltd.)

Background and Aims: A higher frequency of dyslipidemia is reported in children with type 1 diabetes (T1D) and celiac disease (CD). Recently, continuous subcutaneous insulin infusion (CSII) has been associated with better lipid profiles in patients with T1D. The aim of this study was to investigate the association between treatment modality and lipid profile, metabolic control, and body mass index (BMI)-SDS in children with both T1D and CD., Methods: Cross-sectional study in children registered in the international SWEET database in November 2020. Inclusion criteria were children (2-18 years) with T1D and CD with available data on treatment modality (CSII and injections therapy, IT), triglyceride, total cholesterol, HDL, LDL, dyslipidemia, HbA1c, and BMI-SDS. Overweight/obesity was defined as > +1 BMI-SDS for age. Data were analyzed by linear and logistical regression models with adjustment for age, gender, and diabetes duration., Results: In total 1009 children with T1D and CD (female 54%, CSII 54%, age 13.9 years ±3.6, diabetes duration 7.2 years ±4.1, HbA1c 7.9% ±1.4) were included. Significant differences between children treated with CSII vs. IT were respectively found; HDL 60.0 mg/dL vs. 57.8 mg/dL, LDL 89.4 mg/dL vs. 94.2 mg/dL, HbA1c 7.7 vs. 8.1%, BMI-SDS 0.4 vs. 0.6, overweight and obesity 17% vs. 26% (all p < 0.05)., Conclusions: CSII is associated with higher HDL and lower LDL, HbA1c, BMI-SDS, and percentage of overweight and obesity compared with IT in this study. Further prospective studies are required to determine whether CSII improves lipid profile, metabolic control and normalize body weight in children with both T1D and CD.

Type 1 diabetes (T1D) is a known risk factor for fractures, but the underlying pathophysiology is still not fully understood. This study aims to define age peaks and frequent fracture sites of children and young adults with T1D. Additionally, associations of fractures with metabolic and lifestyle factors as well as with additional complications in individuals with T1D were analyzed. A total of 750 individuals with T1D aged ≤25 years with fractures were matched to 3750 patients with T1D without fractures by demographics and insulin regimen. Hemoglobin A1c (HbA1c) values were compared using linear regression, and logistic regression was used to calculate odds ratios (OR) for fractures in individuals with acute complications and diseases. Median (Q1-Q3) age was 12.7 (9.9 to 14.9) years in individuals with fractures and 16.3 (12.6 to 17.8) years in the entire control group with 65% versus 53% males. Peak age for fractures was 7 to <15 years in males and 9 to <11 years in females, which is earlier than reported for the general population. HbA1c (%) was significantly higher in individuals with fractures than in controls (difference of estimated means: 0.26%; 95% confidence interval [CI] 0.07-0.46), especially in postpubertal females (0.68; 0.10-1.26). Significantly higher odds for fractures were observed in individuals with severe hypoglycemia (OR = 1.90; 95% CI 1.47-2.47), especially in prepubertal females (OR = 2.81; 1.21-6.52]) and postpubertal males (2.44; 1.11-5.38), celiac disease (2.02; 1.67-2.45), and with a history of smoking (1.38; 1.02-1.88). The age peak of fractures seems to be earlier in T1D than in the general population. Poor glycemic control is related to fractures, even before puberty. Associations of HbA1c and severe hypoglycemia with fractures highly depend on age and sex. © 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR)., (© 2021 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).)

Objective: To examine the association between the use of diabetes technology (insulin pump [CSII], glucose sensor [CGM] or both) and metabolic control (HbA1c) as well as body adiposity (BMI-SDS) over-time in a cohort of children and adolescents with type 1 diabetes (T1D), that have never used these technologies before., Subjects and Methods: Four thousand six hundred forty three T1D patients (2-18 years, T1D ≥1 year, without celiac disease, no CSII and/or CGM before 2016) participating in the SWEET prospective multicenter diabetes registry, were enrolled. Data were collected at two points (2016; 2019). Metabolic control was assessed by glycated hemoglobin (HbA1c) and body adiposity by BMI-SDS (WHO). Patients were categorized by treatment modality (multiple daily injections [MDI] or CSII) and the use or not of CGM. Linear regression models, adjusted for age, gender, duration of diabetes and region, were applied to assess differences in HbA1c and BMI-SDS among patient groups., Results: The proportion of patients using MDI with CGM and CSII with CGM significantly increased from 2016 to 2019 (7.2%-25.7%, 7.8%-27.8% respectively; p < 0.001). Linear regression models showed a significantly lower HbA1c in groups that switched from MDI to CSII with or without CGM (p < 0.001), but a higher BMI-SDS (from MDI without CGM to CSII with CGM p < 0.05; from MDI without CGM to CSII without CGM p < 0.01)., Conclusions: Switching from MDI to CSII is significantly associated with improvement in glycemic control but increased BMI-SDS over-time. Diabetes technology may improve glucose control in youths with T1D although further strategies to prevent excess fat accumulation are needed., (© 2021 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objectives: With this study, our aim was to quantify the relative risk (RR) of diabetic ketoacidosis at diagnosis of type 1 diabetes during the year 2020 and to assess whether it was associated with the regional incidence of coronavirus disease 2019 (COVID-19) cases and deaths., Methods: Multicenter cohort study based on data from the German Diabetes Prospective Follow-up Registry. The monthly RR for ketoacidosis in 2020 was estimated from observed and expected rates in 3238 children with new-onset type 1 diabetes. Expected rates were derived from data from 2000 to 2019 by using a multivariable logistic trend regression model. The association between the regional incidence of COVID-19 and the rate of ketoacidosis was investigated by applying a log-binomial mixed-effects model to weekly data with Germany divided into 5 regions., Results: The observed versus expected frequency of diabetic ketoacidosis was significantly higher from April to September and in December (mean adjusted RRs, 1.48-1.96). During the first half of 2020, each increase in the regional weekly incidence of COVID-19 by 50 cases or 1 death per 100 000 population was associated with an increase in the RR of diabetic ketoacidosis of 1.40 (95% confidence interval, 1.10-1.77; P = .006) and 1.23 (1.14-1.32; P < .001), respectively. This association was no longer evident during the second half of 2020., Conclusions: These findings suggest that the local severity of the pandemic rather than health policy measures appear to be the main reason for the increase in diabetic ketoacidosis and thus the delayed use of health care during the pandemic., Competing Interests: POTENTIAL CONFLICT OF INTEREST: Prof Raile is an advisory board member of Lilly Diabetes and Abbott Diabetes Care and reports paid talks for Sanofi, Dexcom Continuous Glucose Monitoring, Novo Nordisk, and Springer Healthcare outside the submitted work. Dr Mönkemöller received educational fees from Medtronic outside the submitted work; the other authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2021 by the American Academy of Pediatrics.)

Background: Studies on acute complications in adult T1D were previously reported from the United States (U.S.) and from Germany. The aim was to compare demographic characteristics and patterns of severe hypoglycaemia (SH) and diabetic ketoacidosis (DKA) between Germany and the U.S., Methods: Descriptive comparison on individuals aged ≥18 years, with T1D duration ≥2 years were made between the German diabetes-patient registry (DPV) and the U.S. electronic-health-record database (T1PCO). Individuals in both databases were divided into patients with haemoglobin A1c (HbA1c) <7% and HbA1c ≥7%., Results: 5190 (DPV) and 31,430 individuals (T1PCO) fulfilled the inclusion criteria. DPV patients were younger, more often male and had lower body-mass index. In both databases, more males than females had HbA1c <7%. Individuals had higher HbA1c in T1PCO compared to DPV. The relationship between HbA1c and DKA was similar in both databases. SH revealed a U-shaped curve in T1PCO, but no clear pattern was present in DPV. SH events increased with higher age in DPV, but not in T1PCO., Conclusion: Patterns of SH differ between Germany and U.S. Differences in capture of SH among the databases cannot be excluded, but differences in health care including patient education and level of care by specialists are likely., Competing Interests: Declaration of competing interest J.H.P. is a consultant for Diasome, Insulet, Lexicon, Lilly, MannKind, Novo Nordisk, Sanofi and Senseonics. F.L.Z. is an employee and stockholder of Sanofi. S.V.E. is a medical advisor for AstraZeneca, BrightSight, InPen, Lexicon, Lilly USA LLC, MannKind, Merck, Novo Nordisk and Sanofi; is a speaker for AstraZeneca, Lilly USA LLC, MannKind, Merck and Sanofi; and is an advisory board member for Senseonics and TeamType1. No other potential conflicts of interest relevant to this article were reported., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Extant conifer species may be susceptible to rapid environmental change owing to their long generation times, but could also be resilient due to high levels of standing genetic diversity. Hybridisation between closely related species can increase genetic diversity and generate novel allelic combinations capable of fuelling adaptive evolution. Our study unravelled the genetic architecture of adaptive evolution in a conifer hybrid zone formed between Pinus strobiformis and P. flexilis. Using a multifaceted approach emphasising the spatial and environmental patterns of linkage disequilibrium and ancestry enrichment, we identified recently introgressed and background genetic variants to be driving adaptive evolution along different environmental gradients. Specifically, recently introgressed variants from P. flexilis were favoured along freeze-related environmental gradients, while background variants were favoured along water availability-related gradients. We posit that such mosaics of allelic variants within conifer hybrid zones will confer upon them greater resilience to ongoing and future environmental change and can be a key resource for conservation efforts.

Populus tremuloides is the widest-ranging tree species in North America and an ecologically important component of mesic forest ecosystems displaced by the Pleistocene glaciations. Using phylogeographic analyses of genome-wide SNPs (34,796 SNPs, 183 individuals) and ecological niche modeling, we inferred population structure, ploidy levels, admixture, and Pleistocene range dynamics of P. tremuloides , and tested several historical biogeographical hypotheses. We found three genetic lineages located mainly in coastal-Cascades (cluster 1), east-slope Cascades-Sierra Nevadas-Northern Rockies (cluster 2), and U.S. Rocky Mountains through southern Canadian (cluster 3) regions of the P. tremuloides range, with tree graph relationships of the form ((cluster 1, cluster 2), cluster 3). Populations consisted mainly of diploids (86%) but also small numbers of triploids (12%) and tetraploids (1%), and ploidy did not adversely affect our genetic inferences. The main vector of admixture was from cluster 3 into cluster 2, with the admixture zone trending northwest through the Rocky Mountains along a recognized phenotypic cline (Utah to Idaho). Clusters 1 and 2 provided strong support for the "stable-edge hypothesis" that unglaciated southwestern populations persisted in situ since the last glaciation. By contrast, despite a lack of clinal genetic variation, cluster 3 exhibited "trailing-edge" dynamics from niche suitability predictions signifying complete northward postglacial expansion. Results were also consistent with the "inland dispersal hypothesis" predicting postglacial assembly of Pacific Northwestern forest ecosystems, but rejected the hypothesis that Pacific-coastal populations were colonized during outburst flooding from glacial Lake Missoula. Overall, congruent patterns between our phylogeographic and ecological niche modeling results and fossil pollen data demonstrate complex mixtures of stable-edge, refugial locations, and postglacial expansion within P. tremuloides . These findings confirm and refine previous genetic studies, while strongly supporting a distinct Pacific-coastal genetic lineage of quaking aspen., Competing Interests: None declared., (© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

We implemented multilocus selection in a spatially-explicit, individual-based framework that enables multivariate environmental gradients to drive selection in many loci as a new module for the landscape genetics programs, CDPOP and CDMetaPOP. Our module simulates multilocus selection using a linear additive model, providing a flexible platform to evaluate a wide range of genotype-environment associations. Importantly, the module allows simulation of selection in any number of loci under the influence of any number of environmental variables. We validated the module with individual-based selection simulations under Wright-Fisher assumptions. We then evaluated results for simulations under a simple landscape selection model. Next, we simulated individual-based multilocus selection across a complex selection landscape with three loci linked to three different environmental variables. Finally, we demonstrated how the program can be used to simulate multilocus selection under varying selection strengths across different levels of gene flow in a landscape genetics framework. This new module provides a valuable addition to the study of landscape genetics, allowing for explicit evaluation of the contributions and interactions between gene flow and selection-driven processes across complex, multivariate environmental and landscape conditions., (© 2019 John Wiley & Sons Ltd.)

Understanding migratory connectivity is essential for determining the drivers behind population dynamics and for implementing effective conservation strategies for migratory species. Genetic markers provide a means to describe migratory connectivity; however, they can be uninformative for species with weak population genetic structure, which has limited their application. Here, we demonstrated a genomic approach to describing migratory connectivity in the prothonotary warbler, Protonotaria citrea, a Neotropical songbird of conservation concern. Using 26,189 single nucleotide polymorphisms (SNPs), we revealed regional genetic structure between the Mississippi River Valley and the Atlantic Seaboard with overall weak genetic differentiation among populations (F ST  = 0.0055; 95% CI: 0.0051-0.0059). Genetic variation had a stronger association with geographic rather than environmental factors, with each explaining 14.5% and 8.2% of genetic variation, respectively. By varying the numbers of genomic markers used in population assignment models with individuals of known provenance, we identified a maximum assignment accuracy (89.7% to site, 94.3% to region) using a subset of 600 highly differentiated SNPs. We then assigned samples from nonbreeding sites to breeding region and found low migratory connectivity. Our results highlight the importance of filtering markers for informative loci in models of population assignment. Quantifying migratory connectivity for weakly structured species will be useful for expanding studies to a wider range of migratory species across taxonomic groups and may contribute to a deeper understanding of the evolution of migratory strategies., (© 2019 John Wiley & Sons Ltd.)

The European gypsy moth (Lymantria dispar L.) was first introduced to Massachusetts in 1869 and within 150 years has spread throughout eastern North America. This large-scale invasion across a heterogeneous landscape allows examination of the genetic signatures of adaptation potentially associated with rapid geographical spread. We tested the hypothesis that spatially divergent natural selection has driven observed changes in three developmental traits that were measured in a common garden for 165 adult moths sampled from six populations across a latitudinal gradient covering the entirety of the range. We generated genotype data for 91,468 single nucleotide polymorphisms based on double digest restriction-site associated DNA sequencing and used these data to discover genome-wide associations for each trait, as well as to test for signatures of selection on the discovered architectures. Genetic structure across the introduced range of gypsy moth was low in magnitude (F ST  = 0.069), with signatures of bottlenecks and spatial expansion apparent in the rare portion of the allele frequency spectrum. Results from applications of Bayesian sparse linear mixed models were consistent with the presumed polygenic architectures of each trait. Further analyses indicated spatially divergent natural selection acting on larval development time and pupal mass, with the linkage disequilibrium component of this test acting as the main driver of observed patterns. The populations most important for these signals were two range-edge populations established less than 30 generations ago. We discuss the importance of rapid polygenic adaptation to the ability of non-native species to invade novel environments., (© 2019 John Wiley & Sons Ltd.)

A lack of optimal gene combinations, as well as low levels of genetic diversity, is often associated with the formation of species range margins. Conservation efforts rely on predictive modelling using abiotic variables and assessments of genetic diversity to determine target species and populations for controlled breeding, germplasm conservation and assisted migration. Biotic factors such as interspecific competition and hybridization, however, are largely ignored, despite their prevalence across diverse taxa and their role as key evolutionary forces. Hybridization between species with well-developed barriers to reproductive isolation often results in the production of offspring with lower fitness. Generation of novel allelic combinations through hybridization, however, can also generate positive fitness consequences. Despite this possibility, hybridization-mediated introgression is often considered a threat to biodiversity as it can blur species boundaries. The contribution of hybridization towards increasing genetic diversity of populations at range margins has only recently gathered attention in conservation studies. We assessed the extent to which hybridization contributes towards range dynamics by tracking spatio-temporal changes in the central location of a hybrid zone between two recently diverged species of pines: Pinus strobiformis and P. flexilis . By comparing geographic cline centre estimates for global admixture coefficient with morphological traits associated with reproductive output, we demonstrate a northward shift in the hybrid zone. Using a combination of spatially explicit, individual-based simulations and linkage disequilibrium variance partitioning, we note a significant contribution of adaptive introgression towards this northward movement, despite the potential for differences in regional population size to aid hybrid zone movement. Overall, our study demonstrates that hybridization between recently diverged species can increase genetic diversity and generate novel allelic combinations. These novel combinations may allow range margin populations to track favourable climatic conditions or facilitate adaptive evolution to ongoing and future climate change., Competing Interests: None declared., (© 2019 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.)

As global temperatures rise, thermal limits play an increasingly important role in determining the persistence and spread of invasive species. Gypsy moth (Lymantria dispar L. Lepidoptera: Erebidae) in North America provides an ideal system for studying the effect of high temperatures on invasive species performance. Here, we used fluctuating temperature regimes and exposed gypsy moth at specific points in development (first-fourth instar, pupa) to cycles of favorable (22-28°C) or high-temperature treatments (30-36°C, 32-38°C, 34-40°C) for either 2 or 7 d. We measured survival, growth, and prolonged effects of exposure on development time and pupal mass. Survival generally decreased as the experimental temperature treatment and duration of exposure increased for all instars and pupae, with a narrow threshold for lethal effects. In response to increasing temperature and magnified by longer exposure times, growth abruptly declined for third instars and development time increased for pupae. For those surviving the 2-d exposure treatment, development time to pupation increased for all instars, but we did not find consistent effects on final pupal mass. These negative effects of high temperature provide important data on the susceptibility of gypsy moth to heat at different points in development. This work improves our understanding of thermal limits to growth and development in gypsy moth and can aid in determining invasion potential under current and future climates.

Interactions between extrinsic factors, such as disruptive selection and intrinsic factors, such as genetic incompatibilities among loci, often contribute to the maintenance of species boundaries. The relative roles of these factors in the establishment of reproductive isolation can be examined using species pairs characterized by gene flow throughout their divergence history. We investigated the process of speciation and the maintenance of species boundaries between Pinus strobiformis and Pinus flexilis. Utilizing ecological niche modelling, demographic modelling and genomic cline analyses, we illustrated a divergence history with continuous gene flow. Our results supported an abundance of advanced generation hybrids and a lack of loci exhibiting steep transition in allele frequency across the hybrid zone. Additionally, we found evidence for climate-associated variation in the hybrid index and niche divergence between parental species and the hybrid zone. These results are consistent with extrinsic factors, such as climate, being an important isolating mechanism. A build-up of intrinsic incompatibilities and of coadapted gene complexes is also apparent, although these appear to be in the earliest stages of development. This supports previous work in coniferous species demonstrating the importance of extrinsic factors in facilitating speciation. Overall, our findings lend support to the hypothesis that varying strength and direction of selection pressures across the long lifespans of conifers, in combination with their other life history traits, delays the evolution of strong intrinsic incompatibilities., (© 2018 John Wiley & Sons Ltd.)

Comparing related organisms with differing ecological requirements and evolutionary histories can shed light on the mechanisms and drivers underlying genetic adaptation. Here, by examining a common set of hundreds of loci, we compare patterns of nucleotide diversity and molecular adaptation of two European conifers (Scots pine and maritime pine) living in contrasted environments and characterized by distinct population genetic structure (low and clinal in Scots pine, high and ecotypic in maritime pine) and demographic histories. We found higher nucleotide diversity in Scots pine than in maritime pine, whereas rates of new adaptive substitutions (ω a ), as estimated from the distribution of fitness effects, were similar across species and among the highest found in plants. Sample size and population genetic structure did not appear to have resulted in significant bias in estimates of ω a . Moreover, population contraction-expansion dynamics for each species did not affect differentially the rate of adaptive substitution in these two pines. Several methodological and biological factors may underlie the unusually high rate of adaptive evolution of Scots pine and maritime pine. By providing two new case studies with contrasting evolutionary histories, we contribute to disentangling the multiple factors potentially affecting adaptive evolution in natural plant populations., (© 2017 John Wiley & Sons Ltd.)

Patterns of local adaptation at fine spatial scales are central to understanding how evolution proceeds, and are essential to the effective management of economically and ecologically important forest tree species. Here, we employ single and multilocus analyses of genetic data (n = 116 231 SNPs) to describe signatures of fine-scale adaptation within eight whitebark pine (Pinus albicaulis Engelm.) populations across the local extent of the environmentally heterogeneous Lake Tahoe Basin, USA. We show that despite highly shared genetic variation (F ST  = 0.0069), there is strong evidence for adaptation to the rain shadow experienced across the eastern Sierra Nevada. Specifically, we build upon evidence from a common garden study and find that allele frequencies of loci associated with four phenotypes (mean = 236 SNPs), 18 environmental variables (mean = 99 SNPs), and those detected through genetic differentiation (n = 110 SNPs) exhibit significantly higher signals of selection (covariance of allele frequencies) than could be expected to arise, given the data. We also provide evidence that this covariance tracks environmental measures related to soil water availability through subtle allele frequency shifts across populations. Our results replicate empirical support for theoretical expectations of local adaptation for populations exhibiting strong gene flow and high selective pressures and suggest that ongoing adaptation of many P. albicaulis populations within the Lake Tahoe Basin will not be constrained by the lack of genetic variation. Even so, some populations exhibit low levels of heritability for the traits presumed to be related to fitness. These instances could be used to prioritize management to maintain adaptive potential. Overall, we suggest that established practices regarding whitebark pine conservation be maintained, with the additional context of fine-scale adaptation., (© 2017 John Wiley & Sons Ltd.)

Population genomic analysis can be an important tool in understanding local adaptation. Identification of potential adaptive loci in such analyses is usually based on the survey of a large genomic dataset in combination with environmental variables. Phenotypic data are less commonly incorporated into such studies, although combining a genome scan analysis with a phenotypic trait analysis can greatly improve the insights obtained from each analysis individually. Here, we aimed to identify loci potentially involved in adaptation to climate in 283 Loblolly pine (Pinus taeda) samples from throughout the species' range in the southeastern United States. We analyzed associations between phenotypic, molecular, and environmental variables from datasets of 3082 single nucleotide polymorphism (SNP) loci and 3 categories of phenotypic traits (gene expression, metabolites, and whole-plant traits). We found only 6 SNP loci that displayed potential signals of local adaptation. Five of the 6 identified SNPs are linked to gene expression traits for lignin development, and 1 is linked with whole-plant traits. We subsequently compared the 6 candidate genes with environmental variables and found a high correlation in only 3 of them (R2 > 0.2). Our study highlights the need for a combination of genotypes, phenotypes, and environmental variables, and for an appropriate sampling scheme and study design, to improve confidence in the identification of potential candidate genes., (© The American Genetic Association 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Natural plant populations are often adapted to their local climate and environmental conditions, and populations of forest trees offer some of the best examples of this pattern. However, little empirical work has focused on the relative contribution of single-locus versus multilocus effects to the genetic architecture of local adaptation in plants/forest trees. Here, we employ eastern white pine (Pinus strobus) to test the hypothesis that it is the inter-genic effects that primarily drive climate-induced local adaptation. The genetic structure of 29 range-wide natural populations of eastern white pine was determined in relation to local climatic factors using both a reference set of SSR markers, and SNPs located in candidate genes putatively involved in adaptive response to climate. Comparisons were made between marker sets using standard single-locus outlier analysis, single-locus and multilocus environment association analyses and a novel implementation of Population Graphs. Magnitudes of population structure were similar between the two marker sets. Outlier loci consistent with diversifying selection were rare for both SNPs and SSRs. However, genetic distances based on the multilocus among population covariances (cGD) were significantly more correlated to climate, even after correcting for spatial effects, for SNPs as compared to SSRs. Coalescent simulations confirmed that the differences in mutation rates between SSRs and SNPs did not affect the topologies of the Population Graphs, and hence values of cGD and their correlations with associated climate variables. We conclude that the multilocus covariances among populations primarily reflect adaptation to local climate and environment in eastern white pine. This result highlights the complexity of the genetic architecture of adaptive traits, as well as the need to consider multilocus effects in studies of local adaptation.

Premise of the Study: The ability of California tree populations to survive anthropogenic climate change will be shaped by the geographic structure of adaptive genetic variation. Our goal is to test whether climate-associated candidate genes show evidence of spatially divergent selection in natural populations of valley oak, Quercus lobata, as preliminary indication of local adaptation., Methods: Using DNA from 45 individuals from 13 localities across the species' range, we sequenced portions of 40 candidate genes related to budburst/flowering, growth, osmotic stress, and temperature stress. Using 195 single nucleotide polymorphisms (SNPs), we estimated genetic differentiation across populations and correlated allele frequencies with climate gradients using single-locus and multivariate models., Results: The top 5% of FST estimates ranged from 0.25 to 0.68, yielding loci potentially under spatially divergent selection. Environmental analyses of SNP frequencies with climate gradients revealed three significantly correlated SNPs within budburst/flowering genes and two SNPs within temperature stress genes with mean annual precipitation, after controlling for multiple testing. A redundancy model showed a significant association between SNPs and climate variables and revealed a similar set of SNPs with high loadings on the first axis. In the RDA, climate accounted for 67% of the explained variation, when holding climate constant, in contrast to a putatively neutral SSR data set where climate accounted for only 33%., Conclusions: Population differentiation and geographic gradients of allele frequencies in climate-associated functional genes in Q. lobata provide initial evidence of adaptive genetic variation and background for predicting population response to climate change., (© 2016 Botanical Society of America.)

Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced-representation sequencing, candidate-gene approaches, linearity of allele-environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies., (© 2015 John Wiley & Sons Ltd.)

Background: As it becomes increasingly possible to obtain DNA sequences of orthologous genes from diverse sets of taxa, species trees are frequently being inferred from multilocus data. However, the behavior of many methods for performing this inference has remained largely unexplored. Some methods have been proven to be consistent given certain evolutionary models, whereas others rely on criteria that, although appropriate for many parameter values, have peculiar zones of the parameter space in which they fail to converge on the correct estimate as data sets increase in size., Results: Here, using North American pines, we empirically evaluate the behavior of 24 strategies for species tree inference using three alternative outgroups (72 strategies total). The data consist of 120 individuals sampled in eight ingroup species from subsection Strobus and three outgroup species from subsection Gerardianae, spanning ∼47 kilobases of sequence at 121 loci. Each "strategy" for inferring species trees consists of three features: a species tree construction method, a gene tree inference method, and a choice of outgroup. We use multivariate analysis techniques such as principal components analysis and hierarchical clustering to identify tree characteristics that are robustly observed across strategies, as well as to identify groups of strategies that produce trees with similar features. We find that strategies that construct species trees using only topological information cluster together and that strategies that use additional non-topological information (e.g., branch lengths) also cluster together. Strategies that utilize more than one individual within a species to infer gene trees tend to produce estimates of species trees that contain clades present in trees estimated by other strategies. Strategies that use the minimize-deep-coalescences criterion to construct species trees tend to produce species tree estimates that contain clades that are not present in trees estimated by the Concatenation, RTC, SMRT, STAR, and STEAC methods, and that in general are more balanced than those inferred by these other strategies., Conclusions: When constructing a species tree from a multilocus set of sequences, our observations provide a basis for interpreting differences in species tree estimates obtained via different approaches that have a two-stage structure in common, one step for gene tree estimation and a second step for species tree estimation. The methods explored here employ a number of distinct features of the data, and our analysis suggests that recovery of the same results from multiple methods that tend to differ in their patterns of inference can be a valuable tool for obtaining reliable estimates.

One of the most important drivers of local adaptation for forest trees is climate. Coupled to these patterns, however, are human-induced disturbances through habitat modification and pollution. The confounded effects of climate and disturbance have rarely been investigated with regard to selective pressure on forest trees. Here, we have developed and used a population genetic approach to search for signals of selection within a set of 36 candidate genes chosen for their putative effects on adaptation to climate and human-induced air pollution within five populations of red spruce (Picea rubens Sarg.), distributed across its natural range and air pollution gradient in eastern North America. Specifically, we used FST outlier and environmental correlation analyses to highlight a set of seven single nucleotide polymorphisms (SNPs) that were overly correlated with climate and levels of sulphate pollution after correcting for the confounding effects of population history. Use of three age cohorts within each population allowed the effects of climate and pollution to be separated temporally, as climate-related SNPs (n = 7) showed the strongest signals in the oldest cohort, while pollution-related SNPs (n = 3) showed the strongest signals in the youngest cohorts. These results highlight the usefulness of population genetic scans for the identification of putatively nonneutral evolution within genomes of nonmodel forest tree species, but also highlight the need for the development and application of robust methodologies to deal with the inherent multivariate nature of the genetic and ecological data used in these types of analyses., (© 2013 John Wiley & Sons Ltd.)

A primary goal of evolutionary genetics is to discover and explain the genetic basis of fitness-related traits and how this genetic basis evolves within natural populations. Unprecedented technological advances have fueled the discovery of genetic variants associated with ecologically relevant phenotypes in many different life forms, as well as the ability to scan genomes for deviations from selectively neutral models of evolution. Theoretically, the degree of overlap between lists of genomic regions identified using each approach is related to the genetic architecture of fitness-related traits and the strength and type of natural selection molding variation at these traits within natural populations. Here we address for the first time in a plant the degree of overlap between these lists, using patterns of nucleotide diversity and divergence for >7000 unique amplicons described from the extensive expressed sequence tag libraries generated for loblolly pine (Pinus taeda L.) in combination with the >1000 published genetic associations. We show that loci associated with phenotypic traits are distinct with regard to neutral expectations. Phenotypes measured at the whole plant level (e.g., disease resistance) exhibit an approximately twofold increase in the proportion of adaptive nonsynonymous substitutions over the genome-wide average. As expected for polygenic traits, these signals were apparent only when loci were considered at the level of functional sets. The ramifications of this result are discussed in light of the continued efforts to dissect the genetic basis of quantitative traits.

Estimates from molecular data for the fraction of new nonsynonymous mutations that are adaptive vary strongly across plant species. Much of this variation is due to differences in life history strategies as they influence the effective population size (Ne ). Ample variation for these estimates, however, remains even when comparisons are made across species with similar values of Ne . An open question thus remains as to why the large disparity for estimates of adaptive evolution exists among plant species. Here, we have estimated the distribution of deleterious fitness effects (DFE) and the fraction of adaptive nonsynonymous substitutions (α) for 11 species of soft pines (subgenus Strobus) using DNA sequence data from 167 orthologous nuclear gene fragments. Most newly arising nonsynonymous mutations were inferred to be so strongly deleterious that they would rarely become fixed. Little evidence for long-term adaptive evolution was detected, as all 11 estimates for α were not significantly different from zero. Nucleotide diversity at synonymous sites, moreover, was strongly correlated with attributes of the DFE across species, thus illustrating a strong consistency with the expectations from the Nearly Neutral Theory of molecular evolution. Application of these patterns to genome-wide expectations for these species, however, was difficult as the loci chosen for the analysis were a biased set of conserved loci, which greatly influenced the estimates of the DFE and α. This implies that genome-wide parameter estimates will need truly genome-wide data, so that many of the existing patterns documented previously for forest trees (e.g. little evidence for signature of selection) may need revision., (© 2013 John Wiley & Sons Ltd.)

Variation in the expression of genes with putative roles in wood development was associated with single-nucleotide polymorphisms (SNPs) using a population of loblolly pine (Pinus taeda L.) that included individuals from much of the native range. Association studies were performed using 3938 SNPs and expression data obtained using quantitative real-time polymerase chain reaction (PCR) (qRT-PCR) for 106 xylem development genes in 400 clonally replicated loblolly pine individuals. A general linear model (GLM) approach, which takes the underlying population structure into consideration, was used to discover significant associations. After adjustment for multiple testing using a false discovery rate correction, 88 statistically significant associations (Q<0.05) were observed for 80 SNPs with the expression data of 33 xylem development genes. Thirty SNPs caused nonsynonymous mutations, 18 resulted in synonymous mutations, 11 were in 3' untranslated regions (UTRs), 1 was in a 5' UTR and 20 were in introns. Using AraNet, we found that Arabidopsis genes with high similarity to the loblolly pine genes involved in 21 of the 88 statistically significant associations are connected in functional gene networks. Comparisons of gene expression values revealed that in most cases the average expression in plants homozygous for the rare SNP allele was lower than that of plants that were heterozygous or homozygous for the abundant allele. Although there are association studies of SNPs and expression profiles for humans, Arabidopsis and white spruce, to the best of our knowledge, this is the first example of such an association genetic study in pines. Functional validation of these associations will lead to a deeper understanding of the molecular basis of phenotypic differences in wood development among individuals in conifer populations.

Climate is one of the most important drivers of local adaptation in forest tree species. Standing levels of genetic diversity and structure within and among natural populations of forest trees are determined by the interplay between climatic heterogeneity and the balance between selection and gene flow. To investigate this interplay, single nucleotide polymorphisms (SNPs) were genotyped in 24 to 37 populations from four subalpine conifers, Abies alba Mill., Larix decidua Mill., Pinus cembra L. and Pinus mugo Turra, across their natural ranges in the Italian Alps and Apennines. Patterns of population structure were apparent using a Bayesian clustering program, STRUCTURE, which identified three to five genetic groups per species. Geographical correlates with these patterns, however, were only apparent for P. cembra. Multivariate environmental variables [i.e. principal components (PCs)] were subsequently tested for association with SNPs using a Bayesian generalized linear mixed model. The majority of the SNPs, ranging from six in L. decidua to 18 in P. mugo, were associated with PC1, corresponding to winter precipitation and seasonal minimum temperature. In A. alba, four SNPs were associated with PC2, corresponding to the seasonal minimum temperature. Functional annotation of those genes with the orthologs in Arabidopsis revealed several genes involved in abiotic stress response. This study provides a detailed assessment of population structure and its association with environment and geography in four coniferous species in the Italian mountains., (© 2012 Blackwell Publishing Ltd.)

A candidate gene approach was used to identify levels of nucleotide diversity and to identify genes departing from neutral expectations in coniferous species of the Alpine European forest. Twelve samples were collected from four species that dominate montane and subalpine forests throughout Europe: Abies alba Mill, Larix decidua Mill, Pinus cembra L., and Pinus mugo Turra. A total of 800 genes, originally resequenced in Pinus taeda L., were resequenced across 12 independent trees for each of the four species. Genes were assigned to two categories, candidate and control, defined through homology-based searches to Arabidopsis. Estimates of nucleotide diversity per site varied greatly between polymorphic candidate genes (range: 0.0004-0.1295) and among species (range: 0.0024-0.0082), but were within the previously established ranges for conifers. Tests of neutrality using stringent significance thresholds, performed under the standard neutral model, revealed one to seven outlier loci for each species. Some of these outliers encode proteins that are involved with plant stress responses and form the basis for further evolutionary enquiries.