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Hypertension remains a leading cause of cardiovascular and kidney diseases. Failure to control blood pressure with ≥ 3 medications or control requiring ≥ 4 medications is classified as resistant hypertension (rHTN) and new therapies are needed to reduce the resulting increased risk of morbidity and mortality. Here, we report genetic evidence that relaxin family peptide receptor 2 (RXFP2) is associated with rHTN in men, but not in women. This study shows that adrenal gland gene expression of RXFP2 is increased in men with hypertension and the RXFP2 natural ligand, INSL3, increases adrenal steroidogenesis and corticosteroid secretion in human adrenal cells. To address the hypothesis that RXFP2 activation is an important mechanism in rHTN, we discovered and characterized small molecule and monoclonal antibody (mAb) blockers of RXFP2. The novel chemical entities and mAbs show potent, selective inhibition of RXFP2 and reduce aldosterone and cortisol synthesis and release. The RXFP2 mAbs have suitable rat pharmacokinetic profiles to evaluate the role of RXFP2 in the development and maintenance of rHTN. Overall, we identified RXFP2 activity as a potential new mechanism in rHTN and discovered RXFP2 antagonists for the future interrogation of RXFP2 in cardiovascular and renal diseases., (© 2024. The Author(s).)

Human genetics plays an increasingly important role in drug development and population health. Here we review the history of human genetics in the context of accelerating the discovery of therapies, present examples of how human genetics evidence supports successful drug targets, and discuss how polygenic risk scores could be beneficial in various clinical settings. We highlight the value of direct-to-consumer platforms in the era of fast-paced big data biotechnology, and how diverse genetic and health data can benefit society. © 2021 23andMe, Inc. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland., (© 2021 23andMe, Inc. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.)

We trained and validated risk prediction models for the three major types of skin cancer- basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma-on a cross-sectional and longitudinal dataset of 210,000 consented research participants who responded to an online survey covering personal and family history of skin cancer, skin susceptibility, and UV exposure. We developed a primary disease risk score (DRS) that combined all 32 identified genetic and non-genetic risk factors. Top percentile DRS was associated with an up to 13-fold increase (odds ratio per standard deviation increase >2.5) in the risk of developing skin cancer relative to the middle DRS percentile. To derive lifetime risk trajectories for the three skin cancers, we developed a second and age independent disease score, called DRSA. Using incident cases, we demonstrated that DRSA could be used in early detection programs for identifying high risk asymptotic individuals, and predicting when they are likely to develop skin cancer. High DRSA scores were not only associated with earlier disease diagnosis (by up to 14 years), but also with more severe and recurrent forms of skin cancer.

Twin and family studies have established the contribution of genetic factors to variation in metabolic, hematologic and immunological parameters. The majority of these studies analyzed single or combined traits into pre-defined syndromes. In the present study, we explore an alternative multivariate approach in which a broad range of metabolic, hematologic, and immunological traits are analyzed simultaneously to determine the resemblance of monozygotic (MZ) twin pairs, twin-spouse pairs and unrelated, non-cohabiting individuals. A total of 517 participants from the Netherlands Twin Register, including 210 MZ twin pairs and 64 twin-spouse pairs, took part in the study. Data were collected on body composition, blood pressure, heart rate, and multiple biomarkers assessed in fasting blood samples, including lipid levels, glucose, insulin, liver enzymes, hematological measurements and cytokine levels. For all 51 measured traits, pair-wise Pearson correlations, correcting for family relatedness, were calculated across all the individuals in the cohort. Hierarchical clustering techniques were applied to group the measured traits into sub-clusters based on similarity. Sub-clusters were observed among metabolic traits and among inflammatory markers. We defined a phenotypic profile as the collection of all the traits measured for a given individual. Average within-pair similarity of phenotypic profiles was determined for the groups of MZ twin pairs, spouse pairs and pairs of unrelated individuals. The average similarity across the full phenotypic profile was higher for MZ twin pairs than for spouse pairs, and lowest for pairs of unrelated individuals. Cohabiting MZ twins were more similar in their phenotypic profile compared to MZ twins who no longer lived together. The correspondence in the phenotypic profile is therefore determined to a large degree by familial, mostly genetic, factors, while household factors contribute to a lesser degree to profile similarity.

In multiple sclerosis (MS), lymphocyte--in particular B cell--transit between the central nervous system (CNS) and periphery may contribute to the maintenance of active disease. Clonally related B cells exist in the cerebrospinal fluid (CSF) and peripheral blood (PB) of MS patients; however, it remains unclear which subpopulations of the highly diverse peripheral B cell compartment share antigen specificity with intrathecal B cell repertoires and whether their antigen stimulation occurs on both sides of the blood-brain barrier. To address these questions, we combined flow cytometric sorting of PB B cell subsets with deep immune repertoire sequencing of CSF and PB B cells. Immunoglobulin (IgM and IgG) heavy chain variable (VH) region repertoires of five PB B cell subsets from MS patients were compared with their CSF Ig-VH transcriptomes. In six of eight patients, we identified peripheral CD27(+)IgD(-) memory B cells, CD27(hi)CD38(hi) plasma cells/plasmablasts, or CD27(-)IgD(-) B cells that had an immune connection to the CNS compartment. Pinpointing Ig class-switched B cells as key component of the immune axis thought to contribute to ongoing MS disease activity strengthens the rationale of current B cell-targeting therapeutic strategies and may lead to more targeted approaches., (Copyright © 2014, American Association for the Advancement of Science.)

It has been postulated that aging is the consequence of an accelerated accumulation of somatic DNA mutations and that subsequent errors in the primary structure of proteins ultimately reach levels sufficient to affect organismal functions. The technical limitations of detecting somatic changes and the lack of insight about the minimum level of erroneous proteins to cause an error catastrophe hampered any firm conclusions on these theories. In this study, we sequenced the whole genome of DNA in whole blood of two pairs of monozygotic (MZ) twins, 40 and 100 years old, by two independent next-generation sequencing (NGS) platforms (Illumina and Complete Genomics). Potentially discordant single-base substitutions supported by both platforms were validated extensively by Sanger, Roche 454, and Ion Torrent sequencing. We demonstrate that the genomes of the two twin pairs are germ-line identical between co-twins, and that the genomes of the 100-year-old MZ twins are discerned by eight confirmed somatic single-base substitutions, five of which are within introns. Putative somatic variation between the 40-year-old twins was not confirmed in the validation phase. We conclude from this systematic effort that by using two independent NGS platforms, somatic single nucleotide substitutions can be detected, and that a century of life did not result in a large number of detectable somatic mutations in blood. The low number of somatic variants observed by using two NGS platforms might provide a framework for detecting disease-related somatic variants in phenotypically discordant MZ twins.

Common single-nucleotide polymorphisms (SNPs) at nicotinic acetylcholine receptor (nAChR) subunit genes have previously been associated with measures of nicotine dependence. We investigated the contribution of common SNPs and rare single-nucleotide variants (SNVs) in nAChR genes to Fagerström test for nicotine dependence (FTND) scores in treatment-seeking smokers. Exons of 10 genes were resequenced with next-generation sequencing technology in 448 European-American participants of a smoking cessation trial, and CHRNB2 and CHRNA4 were resequenced by Sanger technology to improve sequence coverage. A total of 214 SNP/SNVs were identified, of which 19.2% were excluded from analyses because of reduced completion rate, 73.9% had minor allele frequencies <5%, and 48.1% were novel relative to dbSNP build 129. We tested associations of 173 SNP/SNVs with the FTND score using data obtained from 430 individuals (18 were excluded because of reduced completion rate) using linear regression for common, the cohort allelic sum test and the weighted sum statistic for rare, and the multivariate distance matrix regression method for both common and rare SNP/SNVs. Association testing with common SNPs with adjustment for correlated tests within each gene identified a significant association with two CHRNB2 SNPs, eg, the minor allele of rs2072660 increased the mean FTND score by 0.6 Units (P=0.01). We observed a significant evidence for association with the FTND score of common and rare SNP/SNVs at CHRNA5 and CHRNB2, and of rare SNVs at CHRNA4. Both common and/or rare SNP/SNVs from multiple nAChR subunit genes are associated with the FTND score in this sample of treatment-seeking smokers.

The analysis of fatty acids from common vegetable oils was investigated for application to forensic casework. A base-catalyzed transesterification of the fatty acids to fatty acid methyl esters using tetramethylammonium hydroxide was simple, rapid, straightforward and inexpensive. Canola, corn, olive, peanut, safflower, soybean and sunflower oils were able to be classified based on their fatty acid methyl ester profiles. Using gas chromatography-mass spectrometry, the detection limits for canola, corn, olive, peanut and safflower oils were determined to be 0.4 mg/mL or less and 0.2 mg/mL or less for soybean and sunflower oils.