Search

Alzheimer's disease (AD) is predicted to affect 132 million people by 2050. Targeting modifiable lifestyle risk factors that are associated with an increased risk of AD could prevent a large proportion of dementia cases, allowing people to reach the end of their life dementia free. However, evidence obtained from the observational studies does not take into account how risk factors are correlated with one another, and whether they causally contribute to increased AD risk. In this study, we determine whether the relationship between previously speculated AD risk factors and AD susceptibility is consistent with causality using large-scale genetic data. We focus on educational attainment (EA), intelligence and household income which have been previously shown to be causally associated with AD. Using GWAS-by-subtraction and Multivariable Mendelian Randomization we show that of these, only the cognitive component of EA (intelligence) is independently causally associated with AD. This work has ramifications for the modifiability of lifestyle risk factors for AD.

Background Major depressive disorder (MDD) is a common and highly heterogeneous psychiatric disorder but little is known about the genetic characterisation of this heterogeneity. Understanding the genetic etiology of MDD can be challenging as large sample sizes are needed for gene discovery – often achieved with a trade-off in the depth phenotyping. Methods The Australian Genetics of Depression Study is the largest stand-alone depression cohort with both genetic data and in-depth phenotyping and comprises a total of 15,792 participants of European ancestry, 92% of whom, met diagnostic criteria for MDD. We leveraged the unique nature of this cohort to conduct a meta-analysis with the largest depression GWAS to date and subsequently used polygenic scores (PGS) to investigate genetic heterogeneity across various clinical subtypes of MDD. Results We increased the number of known genome-wide significant variants associated with depression from 103 to 126 and found evidence of association of novel genes implicated in neuronal development. We show that a PGS for depression explains 5.7% of variance in MDD liability in our sample. Lastly, we find strong support for genetic heterogeneity in depression with differential associations of multiple psychiatric and comorbid traits with age of onset, longitudinal course and various subtypes of MDD. Conclusions Until now, this degree of detailed phenotyping in such a large sample of MDD cases has not been possible. Along with discovery of novel loci, we provide support for differential pathways to illness models that recognize both the overlap with other common psychiatric disorders, as well as pathophysiological differences.

The recruitment of participants for research studies may be subject to bias due to an overrepresentation of those more willing to participate voluntarily. No study has analysed the effect of genetic predisposition to Alzheimer’s disease (AD) on study participation. The Prospective Imaging Study of Ageing (PISA), aims to characterise the phenotype and natural history of healthy adult Australians at high future risk of AD. Participants approached to take part in PISA were selected from existing cohort studies with available genome-wide genetic data for both successfully and unsuccessfully recruited participants, allowing us to investigate the genetic contribution to voluntary recruitment. From a recruitment pool of 13,432 individuals (age 40-80), 64% of participants were successfully recruited into the study. Polygenic risk scores (PRS) were computed in order to test to what extent the genetic risk for AD, and related risk factors (including educational attainment, household income and IQ), predicted participation in PISA. We examined the associations between PRS andAPOEε4 with recruitment using logistic regression models. We found significant associations of age and sex with study participation, where older and female participants were more likely to complete the core module. We did not identify a significant association of genetic risk for AD with study participation. Nonetheless, we identified significant associations with genetic scores for key causal risk factors for AD, such as IQ, household income and years of education. Our findings highlight the importance of considering bias in key risk factors for AD in the recruitment of individuals for cohort studies.

Deciphering the genetic architecture of depression is pivotal for characterizing the associated pathophysiological processes and development of new therapeutics. Here we conducted a cross-ancestry genome-wide meta-analysis on depression (416,437 cases and 1,308,758 controls) and identified 287 risk loci, of which 140 are new. Variant-level fine-mapping prioritized potential causal variants and functional genomic analysis identified variants that regulate the binding of transcription factors. We validated that 80% of the identified functional variants are regulatory variants and expression quantitative trait loci (eQTL) analysis uncovered the potential target genes regulated by the prioritized risk variants. Gene-level analysis, including transcriptome-wide association study (TWAS), proteome-wide association study (PWAS), colocalization and Mendelian randomization-based analyses, prioritized potential causal genes and drug targets. Combining evidence from different analyses revealed likely causal genes, includingTMEM106B, CTNND1, EPHB2, AREL1, CSE1L, RAB27B, SATU1, TMEM258, DCC, etc. Pathway analysis showed significant enrichment of depression risk genes in synapse-related pathways. Finally, we showed thatTmem106bknockdown resulted in depression-like behaviors in mice, supporting involvement ofTmem106bin depression. Our study identified new risk loci, likely causal variants and genes for depression, providing important insights into the genetic architecture of depression and potential therapeutic targets.

Background Variation within the CYP2C19 gene has been linked to differential metabolism of selective serotonin reuptake inhibitors (SSRIs). Pharmacogenetic recommendations based on the effect of CYP2C19 variants have been made available and are used increasingly by clinical practitioners. Nonetheless, the underlying assumption linking differential metabolism to efficacy or adverse side effects remains understudied. Here, we aim to fill this gap by studying CYP2C19 polymorphisms and inferred metabolism and patient-reported antidepressant response in a sample of 9531 Australian adults who have taken SSRIs. Methods Metaboliser status was inferred for participants based on CYP2C19 alleles. Primary analysis consisted of assessing differences in treatment efficacy and tolerability between normal (reference) and: ultrarapid, rapid, intermediate and poor metabolisers. Results Across medications, poor metabolisers reported a higher efficacy, whereas rapid metabolisers reported higher tolerability. When stratified by drug, associations between metaboliser status and efficacy did not survive multiple testing correction. Intermediate metabolisers were at greater odds of reporting any side effect for sertraline and higher number of side effects across medications and for sertraline. Conclusions The effects between metaboliser status and treatment efficacy, tolerability and side effects were in the expected direction. Our power analysis suggests we would detect moderate to large effects, at least nominally. Reduced power may also be explained by heterogeneity in antidepressant dosages or concomitant medications, which we did not measure. The fact that we identify slower metabolisers to be at higher risk of side effects even without adjusting for clinical titration, and the nominally significant associations consistent with the expected metabolic effects provide new evidence for the link between CYP2C19 metabolism and SSRI response. Nonetheless, longitudinal and interventional designs such as randomized clinical trials that stratify by metaboliser status are necessary to establish the effects of CYP2C19 metabolism on SSRI treatment efficacy or adverse effects.

Study ObjectivesDespite its association with severe health conditions, the etiology of sleep apnea (SA) remains understudied. This study sought to identify genetic variants robustly associated with SA risk.MethodsWe performed a genome-wide association study (GWAS) meta-analysis of SA across five cohorts (NTotal = 523 366), followed by a multi-trait analysis of GWAS (multi-trait analysis of genome-wide association summary statistics [MTAG]) to boost power, leveraging the high genetic correlation between SA and snoring. We then adjusted our results for the genetic effects of body mass index (BMI) using multi-trait-based conditional and joint analysis (mtCOJO) and sought replication of lead hits in a large cohort of participants from 23andMe, Inc (NTotal = 1 477 352; Ncases = 175 522). We also explored genetic correlations with other complex traits and performed a phenome-wide screen for causally associated phenotypes using the latent causal variable method.ResultsOur SA meta-analysis identified five independent variants with evidence of association beyond genome-wide significance. After adjustment for BMI, only one genome-wide significant variant was identified. MTAG analyses uncovered 49 significant independent loci associated with SA risk. Twenty-nine variants were replicated in the 23andMe GWAS adjusting for BMI. We observed genetic correlations with several complex traits, including multisite chronic pain, diabetes, eye disorders, high blood pressure, osteoarthritis, chronic obstructive pulmonary disease, and BMI-associated conditions.ConclusionOur study uncovered multiple genetic loci associated with SA risk, thus increasing our understanding of the etiology of this condition and its relationship with other complex traits.

It is long known that inbreeding increases the detrimental effects of recessive sequence variants in “Runs of Homozygosity” (ROHs). However, although the phenotypic association of ROH has been investigated for a variety of traits, the statistical power of the results often remains limited as a sufficiently high number of cases are available for only a restricted number of traits. In the present study, we aim to analyze the association of runs of homozygosity with the trait “in-group ethnic favoritism”. This analysis assumes that if ethnic identity is important for an individual, that individual may tend to marry more frequently within their own group and therefore ROH are expected to increase. We hypothesize that an attitude preferring one’s own ethnic group may be associated with a stronger tendency of inbreeding and, as a result, with more and longer ROHs. Accordingly, we investigated the association between the attitude to someone’s own ethnicity and ROH, using the Wisconsin Longitudinal data (WLS, total N ~ 9000) as discovery data set and the Brisbane Twin data as replication data set (N ~ 8000). We find that both the number as well as the total length of homozygous segments are significantly positively associated with “in-group ethnic favoritism”, independent of the method used for ROH calculation. Supplementary Information The online version contains supplementary material available at 10.1007/s10519-021-10053-z.

The Classical Twin Method (CTM) compares the similarity of monozygotic (MZ) twins with that of dizygotic (DZ) twins to make inferences about the relative importance of genes and environment in the etiology of individual differences. The design has been applied to thousands of traits across the biomedical, behavioral and social sciences and is arguably the most widely used natural experiment known to science. The fundamental assumption of the CTM is that trait relevant environmental covariation within MZ pairs is the same as that found within DZ pairs, so that zygosity differences in within-pair variance must be due to genetic factors uncontaminated by the environment. This equal environments assumption (EEA) has been, and still is hotly contested, and has been mentioned as a possible contributing factor to the missing heritability conundrum. In this manuscript, we introduce a new model for testing the EEA, which we call the Augmented Classical Twin Design which uses identity by descent (IBD) sharing between DZ twin pairs to estimate separate environmental variance components for MZ and DZ twin pairs, and provides a test of whether these are equal. We show through simulation that given large samples of DZ twin pairs, the model provides unbiased estimates of variance components and valid tests of the EEA under strong assumptions (e.g. no epistatic variance, IBD sharing in DZ twins estimated accurately etc.) which may not hold in reality. Sample sizes in excess of 50,000 DZ twin pairs with genome-wide genetic data are likely to be required in order to detect substantial violations of the EEA with moderate power. Consequently, we recommend that the Augmented Classical Twin Design only be applied to datasets with very large numbers of DZ twin pairs (> 50,000 DZ twin pairs), and given the strong assumptions relating to the absence of epistatic variance, appropriate caution be exercised regarding interpretation of the results.

The ‘16Up’ study conducted at the QIMR Berghofer Medical Research Institute from January 2014 to December 2018 aimed to examine the physical and mental health of young Australian twins aged 16−18 years (N = 876; 371 twin pairs and 18 triplet sets). Measurements included online questionnaires covering physical and mental health as well as information and communication technology (ICT) use, actigraphy, sleep diaries and hair samples to determine cortisol concentrations. Study participants generally rated themselves as being in good physical (79%) and mental (73%) health and reported lower rates of psychological distress and exposure to alcohol, tobacco products or other substances than previously reported for this age group in the Australian population. Daily or near-daily online activity was almost universal among study participants, with no differences noted between males and females in terms of frequency or duration of internet access. Patterns of ICT use in this sample indicated that the respondents were more likely to use online information sources for researching physical health issues than for mental health or substance use issues, and that they generally reported partial levels of satisfaction with the mental health information they found online. This suggests that internet-based mental health resources can be readily accessed by adolescent Australians, and their computer literacy augurs well for future access to online health resources. In combination with other data collected as part of the ongoing Brisbane Longitudinal Twin Study, the 16Up project provides a valuable resource for the longitudinal investigation of genetic and environmental contributions to phenotypic variation in a variety of human traits.

PurposeParkinson’s disease (PD) is a neurodegenerative disorder associated with progressive disability. While the precise aetiology is unknown, there is evidence of significant genetic and environmental influences on individual risk. The Australian Parkinson’s Genetics Study seeks to study genetic and patient-reported data from a large cohort of individuals with PD in Australia to understand the sociodemographic, genetic and environmental basis of PD susceptibility, symptoms and progression.ParticipantsIn the pilot phase reported here, 1819 participants were recruited through assisted mailouts facilitated by Services Australia based on having three or more prescriptions for anti-PD medications in their Pharmaceutical Benefits Scheme records. The average age at the time of the questionnaire was 64±6 years. We collected patient-reported information and sociodemographic variables via an online (93% of the cohort) or paper-based (7%) questionnaire. One thousand five hundred and thirty-two participants (84.2%) met all inclusion criteria, and 1499 provided a DNA sample via traditional post.Findings to date65% of participants were men, and 92% identified as being of European descent. A previous traumatic brain injury was reported by 16% of participants and was correlated with a younger age of symptom onset. At the time of the questionnaire, constipation (36% of participants), depression (34%), anxiety (17%), melanoma (16%) and diabetes (10%) were the most reported comorbid conditions.Future plansWe plan to recruit sex-matched and age-matched unaffected controls, genotype all participants and collect non-motor symptoms and cognitive function data. Future work will explore the role of genetic and environmental factors in the aetiology of PD susceptibility, onset, symptoms, and progression, including as part of international PD research consortia.

This study assessed the heritability of 25 hydroxyvitamin D3 (25(OH)D3) in a large twin cohort and the shared effect of sun exposure and skin colour on 25(OH)D3 variance. Study participants included 1604 twin pairs and their siblings (n = 4020). Twin correlations for 25(OH)D3 concentration were rMZ=0.79 (584 pairs) and rDZ = 0.52 (1020 pairs) consistent with an average h2 = 0.50 throughout the year. Significant phenotypic and genetic seasonal fluctuation was observed in 25(OH)D3 concentrations with heritability decreasing during the winter (h2 = 0.37) compared to summer (h2 = 0.62). Skin colour (measured both ordinally and quantitatively) and self-reported sun exposure were found to significantly affect 25(OH)D3 concentration. Twins with olive/dark skin had significantly lower 25(OH)D3 concentrations than those with fair/pale skin and multivariate genetic analysis showed that approximately half of the total additive genetic variation in 25(OH)D3 results from genes whose primary influence is on skin colour and sun exposure. Additionally, 37% of the total variance was attributed to shared environmental effects on vitamin D, skin colour and sun exposure measures. These results support a moderate estimate of vitamin D heritability and suggest significant influence of season, skin colour and sun exposure on the genetic variance.

Genes play an important role in children’s cognitive ability through puberty and into adolescence. Recent advances in genomics has enabled us to test the effect of various genetic predispositions on measured cognitive outcomes. Here, we leveraged summary statistics from the most recent genome-wide association studies of eleven cognitive and mental health traits to build polygenic prediction models of measured intelligence and academic achievement in a cohort of Australian adolescent twins (N=2,335, 57% female). Additionally, we tested the association of these polygenic risk scores (PRS) with core academic skills such as the ability to comprehend, structure and sequence, evaluate and assess, communicate, and apply techniques and procedures. We show that PRSs for educational attainment, intelligence and cognitive factors explained up to 10% of the variance in educational achievement and 7% in intelligence test scores in our cohort. Additionally, we found that a genetic predisposition for ADHD was negatively associated with all cognitive outcomes and skills and a genetic predisposition for schizophrenia was negatively associated with performance IQ but no other cognitive domain. In this study, we show the potential value of genotypic data for predicting pupil achievement and cognitive developmental trajectory through puberty and into adolescence. We provide evidence that a genetic vulnerability to some mental health disorders is associated with poorer cognitive and educational outcomes, regardless of whether the individual has developed the disorder.

Variation within the CYP2C19 gene has been linked to differential metabolism of selective serotonin reuptake inhibitors (SSRIs). Pharmacogenetic recommendations based on the effect of CYP2C19 variants have been made available and are used increasingly by clinical practitioners. Nonetheless, the underlying assumption linking differential metabolism to efficacy or adverse side effects remains understudied. Here, we aim to fill this gap by studying CYP2C19 polymorphisms and inferred metabolism and patient-reported antidepressant response in a sample of 9531 Australian adults who have taken SSRIs.Metaboliser status was inferred for participants based on CYP2C19 alleles. Primary analysis consisted of assessing differences in treatment efficacy and tolerability between normal (reference) and: ultrarapid, rapid, intermediate and poor metabolisers.Across medications, poor metabolisers reported a higher efficacy, whereas rapid metabolisers reported higher tolerability. When stratified by drug, associations between metaboliser status and efficacy did not survive multiple testing correction. Intermediate metabolisers were at greater odds of reporting any side effect for sertraline and higher number of side effects across medications and for sertraline.The effects between metaboliser status and treatment efficacy, tolerability and side effects were in the expected direction. Our power analysis suggests we would detect moderate to large effects, at least nominally. Reduced power may also be explained by heterogeneity in antidepressant dosages or concomitant medications, which we did not measure. The fact that we identify slower metabolisers to be at higher risk of side effects even without adjusting for clinical titration, and the nominally significant associations consistent with the expected metabolic effects provide new evidence for the link between CYP2C19 metabolism and SSRI response. Nonetheless, longitudinal and interventional designs such as randomized clinical trials that stratify by metaboliser status are necessary to establish the effects of CYP2C19 metabolism on SSRI treatment efficacy or adverse effects.

Acne vulgaris is a highly heritable skin disorder that primarily impacts facial skin. Severely inflamed lesions may leave permanent scars that have been associated with long-term psychosocial consequences. Here, we perform a GWAS meta-analysis comprising 20,165 individuals with acne from nine independent European ancestry cohorts. We identify 29 novel genome-wide significant loci and replicate 14 of the 17 previously identified risk loci, bringing the total number of reported acne risk loci to 46. Using fine-mapping and eQTL colocalisation approaches, we identify putative causal genes at several acne susceptibility loci that have previously been implicated in Mendelian hair and skin disorders, including pustular psoriasis. We identify shared genetic aetiology between acne, hormone levels, hormone-sensitive cancers and psychiatric traits. Finally, we show that a polygenic risk score calculated from our results explains up to 5.6% of the variance in acne liability in an independent cohort.

PurposeParkinson’s disease (PD) is a neurodegenerative disorder associated with progressive disability. While the precise aetiology is unknown, there is evidence of significant genetic and environmental influences on individual risk. The Australian Parkinson’s Genetics Study (APGS) seeks to study genetic and patient-reported data from a large cohort of individuals with PD in Australia to understand the sociodemographic, genetic, and environmental basis of PD susceptibility, symptoms and progression.ParticipantsIn the pilot phase reported here, 1,819 participants were recruited through assisted mailouts facilitated by Services Australia based on having three or more prescriptions for anti-PD medications in their Pharmaceutical Benefits Scheme (PBS) records. The average age at the time of the questionnaire was 64 ± 6 years. We collected patient-reported PD information and socio-demographic variables via an online (93% of the cohort) or paper-based (7%) questionnaire. One thousand five hundred thirty-two participants (84.2%) met all inclusion criteria, and 1,499 provided a DNA sample via traditional post.Findings to date65% of participants were male, and 92% identified as being of European descent. A previous traumatic brain injury was reported by 16% of participants and was correlated with a younger age of symptom onset. At the time of the questionnaire, constipation (36% of participants), depression (34%), anxiety (17%), melanoma (16%) and diabetes (10%) were the most reported comorbid conditions.Future plansWe plan to recruit sex- and age-matched unaffected controls, genotype all participants, and collect non-motor symptoms and cognitive function data. Future work will explore the role of genetic and environmental factors in the aetiology of PD susceptibility, onset, symptoms, and progression, including as part of international PD research consortia.Article summaryStrengths and limitations of this studyWe used a time- and cost-effective recruitment method that enabled us to reach out to a random sample of individuals who have been prescribed medications for Parkinson’s disease across all over Australia to invite them to participate in this study.The identities of letter recipients remained private and confidential and were not shared with the researchers. However, those recipients who were interested and willing to participate were directed to a website where they could sign up and provide informed consent.The source database only captures individuals who have been prescribed medications to treat Parkinson’s disease in Australia and who are eligible for Medicare. Those without an official diagnosis, not receiving treatment, or not eligible for government subsidies are not included.We collected a wide range of patient-reported variables relevant to disease onset, diagnosis, symptoms, medical comorbidities, lifestyle, and family history in a large cohort of participants. However, some variables might not be as accurate as when measured by a specialist clinician.Given the 9% response rate to our single-letter invitation, there is a substantial risk of self-selection bias. Thus, patient characteristics for this cohort might differ from those of the typical population of individuals with Parkinson’s disease in Australia.

Genome-wide association studies (GWAS) have identified genetic variants associated with brain morphology and substance use behaviors (SUB). However, the genetic overlap between brain structure and SUB has not been well characterized. We leveraged GWAS summary data of 71 brain imaging measures and alcohol, tobacco, and cannabis use to investigate their genetic overlap using linkage disequilibrium score regression. We used genomic structural equation modeling to model a “common SUB genetic factor” and investigated its genetic overlap with brain structure. Furthermore, we estimated SUB polygenic risk scores (PRS) and examined whether they predicted brain imaging traits using the Adolescent Behavior and Cognitive Development (ABCD) study. We identified 8 significant negative genetic correlations, including between (1) alcoholic drinks per week and average cortical thickness, and (2) intracranial volume with age of smoking initiation. We observed 5 positive genetic correlations, including those between (1) insula surface area and lifetime cannabis use, and (2) the common SUB genetic factor and pericalcarine surface area. SUB PRS were associated with brain structure variation in ABCD. Our findings highlight a shared genetic etiology between cortical brain morphology and SUB and suggest that genetic variants associated with SUB may be causally related to brain structure differences.

OBJECTIVES: Network analysis is increasingly applied to psychopathology research. We used it to examine the core phenomenology of emerging bipolar disorder (BD I and II) and ‘at risk’ presentations (major depression with a family history of BD). METHODOLOGY: The study sample comprised a community cohort of 1867 twin and non-twin siblings (57% female; mean age ~26) who had completed self-report ratings of (i) depression-like, hypomanic-like and psychotic-like experiences; (ii) family history of BD; and (iii) were assessed for mood and psychotic syndromes using the Composite International Diagnostic Interview (CIDI). Symptom networks were compared for recent onset BD versus other cohort members and then for individuals at risk of BD (depression with/without a family history of BD). RESULTS: The four key symptoms that differentiated recent onset BD from other cohort members were: anergia, psychomotor speed, hypersomnia and (less) loss of confidence. The four key symptoms that differentiated individuals at high risk of BD from unipolar depression were: anergia, psychomotor speed, impaired concentration, and hopelessness. However, the latter network was less stable and more error prone. CONCLUSIONS: We are encouraged by the overlaps between our findings and those from two recent publications reporting network analyses of BD psychopathology, especially as the studies recruited from different populations and employed different network models. However, the advantages of applying network analysis to youth mental health cohorts (which include many individuals with multi-morbidity) must be weighed against the disadvantages including basic issues such as judgements regarding the selection of items for inclusion in network models.

Risky behaviors, such as substance use and unprotected sex, are associated with various physical and mental health problems. Recent genome‐wide association studies indicated that variation in the cell adhesion molecule 2 (CADM2) gene plays a role in risky behaviors and self‐control. In this phenome‐wide scan for risky behavior, it was tested if underlying common vulnerability could be (partly) explained by pleiotropic effects of this gene and how large the effects were. Single nucleotide polymorphism (SNP)‐level and gene‐level association tests within four samples (25 and Up, Spit for Science, Netherlands Twin Register, and UK Biobank and meta‐analyses over all samples (combined sample of 362,018 participants) were conducted to test associations between CADM2, substance‐ and sex‐related risk behaviors, and various measures related to self‐control. We found significant associations between the CADM2 gene, various risky behaviors, and different measures of self‐control. The largest effect sizes were found for cannabis use, sensation seeking, and disinhibition. Effect sizes ranged from 0.01% to 0.26% for single top SNPs and from 0.07% to 3.02% for independent top SNPs together, with sufficient power observed only in the larger samples and meta‐analyses. In the largest cohort, we found indications that risk‐taking proneness mediated the association between CADM2 and latent factors for lifetime smoking and regular alcohol use. This study extends earlier findings that CADM2 plays a role in risky behaviors and self‐control. It also provides insight into gene‐level effect sizes and demonstrates the feasibility of testing mediation. These findings present a good starting point for investigating biological etiological pathways underlying risky behaviors., CADM2 plays a role in risky behaviors and self‐control. This contributes to unravelling the biological etiological pathways underlying risky behaviors.

The Classical Twin Method (CTM) compares the similarity of monozygotic (MZ) twins with that of dizygotic (DZ) twins to make inferences about the relative importance of genes and environment in the etiology of individual differences. The design has been applied to thousands of traits across the biomedical, behavioral and social sciences and is arguably the most widely used natural experiment known to science. The fundamental assumption of the CTM is that trait relevant environmental covariation within MZ pairs is the same as that found within DZ pairs, so that zygosity differences in within-pair variance must be due to genetic factors uncontaminated by the environment. This equal environments assumption (EEA) has been, and still is hotly contested, and has been mentioned as a possible contributing factor to the missing heritability conundrum. In this manuscript, we introduce a new model for testing the EEA, which we call the Augmented Classical Twin Design which uses identity by descent (IBD) sharing between DZ twin pairs to estimate separate environmental variance components for MZ and DZ twin pairs, and provides a test of whether these are equal. We show through simulation that given large samples of DZ twin pairs, the model provides unbiased estimates of variance components and valid tests of the EEA under strong assumptions (e.g. no epistatic variance, IBD sharing in DZ twins estimated accurately etc.) which may not hold in reality. Sample sizes in excess of 50,000 DZ twin pairs with genome-wide genetic data are likely to be required in order to detect substantial violations of the EEA with moderate power. Consequently, we recommend that the Augmented Classical Twin Design only be applied to datasets with very large numbers of DZ twin pairs ( 50,000 DZ twin pairs), and given the strong assumptions relating to the absence of epistatic variance, appropriate caution be exercised regarding interpretation of the results.

Vitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identify 143 independent loci in 112 1-Mb regions, providing insights into the physiology of vitamin D and implicating genes involved in lipid and lipoprotein metabolism, dermal tissue properties, and the sulphonation and glucuronidation of 25OHD. Mendelian randomization models find no robust evidence that 25OHD concentration has causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes have (direct or indirect) causal effects on 25OHD concentration, clarifying the epidemiological relationship between 25OHD status and the health outcomes examined in this study., Vitamin D is a precursor of the steroid hormone 1,25-dihydroxyvitamin D3, and its deficiency is associated with many adverse health outcomes. Here, Revez et al. perform a genome-wide association study for circulating 25-hydroxyvitamin D in 417,580 individuals and test for potential causal relationships with other traits using Mendelian randomization.

IMPORTANCE: Genetic studies with broad definitions of depression may not capture genetic risk specific to major depressive disorder (MDD), raising questions about how depression should be operationalized in future genetic studies. OBJECTIVE: To use a large, well-phenotyped single study of MDD to investigate how different definitions of depression used in genetic studies are associated with estimation of MDD and phenotypes of MDD, using polygenic risk scores (PRSs). DESIGN, SETTING, AND PARTICIPANTS: In this case-control polygenic risk score analysis, patients meeting diagnostic criteria for a diagnosis of MDD were drawn from the Australian Genetics of Depression Study, a cross-sectional, population-based study of depression, and controls and patients with self-reported depression were drawn from QSkin, a population-based cohort study. Data analyzed herein were collected before September 2018, and data analysis was conducted from September 10, 2020, to January 27, 2021. MAIN OUTCOME AND MEASURES: Polygenic risk scores generated from genome-wide association studies using different definitions of depression were evaluated for estimation of MDD in and within individuals with MDD for an association with age at onset, adverse childhood experiences, comorbid psychiatric and somatic disorders, and current physical and mental health. RESULTS: Participants included 12 106 (71% female; mean age, 42.3 years; range, 18-88 years) patients meeting criteria for MDD and 12 621 (55% female; mean age, 60.9 years; range, 43-87 years) control participants with no history of psychiatric disorders. The effect size of the PRS was proportional to the discovery sample size, with the largest study having the largest effect size with the odds ratio for MDD (1.75; 95% CI, 1.73-1.77) per SD of PRS and the PRS derived from ICD-10 codes documented in hospitalization records in a population health cohort having the lowest odds ratio (1.14; 95% CI, 1.12-1.16). When accounting for differences in sample size, the PRS from a genome-wide association study of patients meeting diagnostic criteria for MDD and control participants was the best estimator of MDD, but not in those with self-reported depression, and associations with higher odds ratios with childhood adverse experiences and measures of somatic distress. CONCLUSIONS AND RELEVANCE: These findings suggest that increasing sample sizes, regardless of the depth of phenotyping, may be most informative for estimating risk of depression. The next generation of genome-wide association studies should, like the Australian Genetics of Depression Study, have both large sample sizes and extensive phenotyping to capture genetic risk factors for MDD not identified by other definitions of depression.

Introduction Hearing loss has been identified as the potentially largest modifiable risk factor for Alzheimer's disease (AD), estimated to account for a similar increase in AD risk as the apolipoprotein E (APOE) gene. Methods We investigated the genetic relationship between hearing loss and AD, and sought evidence for a causal relationship. Results We found a significant genetic overlap between hearing impairment and AD and a polygenic risk score for AD was able to significantly predict hearing loss in an independent cohort. Additionally, regions of the genome involved in inflammation were identified to be shared between hearing difficulty and AD. However, causality tests found no significant evidence of a causal relationship between these traits in either direction. Discussion Overall, these results show that the relationship between hearing difficulty and AD may, in part, be due to shared genes and immune response pathways between the traits. However, currently available data do not support a causal relationship.

Purpose of review: Advances in personal genomics have made predictive genetic testing increasingly popular. The purpose of this review is to examine and summarize recent literature regarding the ethical concerns and considerations surrounding genetic testing for Alzheimer's disease. Recent findings: Four basic bioethical principles can be applied in the context of genetic testing: autonomy, nonmaleficence, beneficence and justice. The concepts of clinical validity, clinical utility and personal utility are also necessary for the ethical deliberation of genetic testing for Alzheimer's disease. Ethical considerations can differ among three distinct settings present in the literature: research, clinical and direct-to-consumer services. Studies have found that the negative psychosocial impact of genetic test results on the individual is limited, but emphasize the importance of pre/posttesting genetic counselling. Summary: The literature should ideally inform policy-making around genetic testing. There exists an urgent need for regulation, particularly in the direct-to-consumer (DTC) market, since interest for testing in this context is rapidly growing. Standardized protocols for disclosure should be developed, and there is a need to find ways to meet the growing need for genetic counselling. Importantly, comprehensive, evidence-based regulation requires that research be conducted in different contexts with more diverse participants.

The aim of the 25 and Up (25Up) study was to assess a wide range of psychological and behavioral risk factors behind mental illness in a large cohort of Australian twins and their non-twin siblings. Participants had already been studied longitudinally from the age of 12 and most recently in the 19Up study (mean age = 26.1 years, SD = 4.1, range = 20–39). This subsequent wave follows up these twins several years later in life (mean age = 29.7 years, SD = 2.2, range = 22–44). The resulting data set enables additional detailed investigations of genetic pathways underlying psychiatric illnesses in the Brisbane Longitudinal Twin Study (BLTS). Data were collected between 2016 and 2018 from 2540 twins and their non-twin siblings (59% female, including 341 monozygotic complete twin-pairs, 415 dizygotic complete pairs and 1028 non-twin siblings and singletons). Participants were from South-East Queensland, Australia, and the sample was of predominantly European ancestry. The 25Up study collected information on 20 different mental disorders, including depression, anxiety, substance use, psychosis, bipolar and attention-deficit hyper-activity disorder, as well as general demographic information such as occupation, education level, number of children, self-perceived IQ and household environment. In this article, we describe the prevalence, comorbidities and age of onset for all 20 examined disorders. The 25Up study also assessed general and physical health, including physical activity, sleep patterns, eating behaviors, baldness, acne, migraines and allergies, as well as psychosocial items such as suicidality, perceived stress, loneliness, aggression, sleep–wake cycle, sexual identity and preferences, technology and internet use, traumatic life events, gambling and cyberbullying. In addition, 25Up assessed female health traits such as morning sickness, breastfeeding and endometriosis. Furthermore, given that the 25Up study is an extension of previous BLTS studies, 86% of participants have already been genotyped. This rich resource will enable the assessment of epidemiological risk factors, as well as the heritability and genetic correlations of mental conditions.

Accurate prediction of hurricane tracks may require resolving the flow both within and around the storm. Since the spatial scales in these two regions differ substantially, uniform resolution is inherently inefficient: the grid should be refined only near the storm. This paper describes the performance of a barotropic model with an adaptive multi-grid scheme which automatically refines the mesh around the storm as it moves. The model is formulatedl on a section of the sphere using a Mercator projection. The model consists of a modified barotropic vorticity equation.