Biology subjects

Straub, P.

Publications and source records attributed to Straub, P..

5 recordsLinked to original sources

bioRxiv2024

Sex differences in immune function and disease risk are not easily explained by an evolutionary mismatch

The "Pregnancy Compensation Hypothesis" (PCH) posits that sex differences in the mammalian immune system reflect the effects of selection on female immunity during pregnancy, during which increased immunomodulation is required to reduce immune responses to the fetus, while maintaining the ability to respond to pathogens. In humans, fewer pathogens and lower parity in urban, industrialized environments has been suggested to leave female immune systems under-stimulated, creating an "evolutionary mismatch" which exacerbates sex differences in immunity and increases female autoimmune disease risk. Yet, robust tests of this mismatch hypothesis have not been conducted. Here, we first confirmed a sex-bias in autoimmune disease prevalence in a large dataset of individuals from the United Kingdom (UK Biobank). Second, we asked whether sex differences in immune function are affected by shifts toward urban, lower-parity lifestyles in a single population--the Turkana people of northwest Kenya. We found that lifestyle alters sex differences in immune cell type proportions, but not in gene expression levels. Contrary to expectations from the PCH, parity did not predict immune physiology. We then tested for generalizable trends across natural fertility mammalian populations versus urban humans (data from Turkana, NHANES, GTEx, Batwa and Bakiga, yellow baboons, and macaques). We did not find consistent relationships between lifestyle and sex-biases in immune biomarkers or between parity and the same immune outcomes. Indeed, we found that parity predicts autoimmune disease risk in the opposite direction than expected from the PCH, with higher parity associated with higher autoimmune disease risk while adjusting for relevant socioeconomic variables in the UK Biobank. Taken together, our work suggests that while sex clearly influences immune physiology and disease risk in urban settings, these effects are not easily explained by an evolutionary mismatch. Future work addressing how sex interacts with lifestyle change to generate disease is needed.

evolutionary biology↗

bioRxiv2022

Investigating community formation through dense spatial and temporal sampling of 5-6th century cemeteries in Pannonia

As the collapse of the Western Roman Empire accelerated during the 4th and 5th centuries, arriving "barbarian" groups began to establish new communities in the border provinces of the declining (and eventually former) empire. This was a time of significant cultural and political change throughout not only these border regions but Europe as a whole.1,2 To better understand post-Roman community formation in one of these key frontier zones after the collapse of the Hunnic movement, we generated new paleogenomic data for a set of 38 burials from a time series of three 5th century cemeteries3-5 at Lake Balaton, Hungary. We utilized a comprehensive sampling approach to characterize these cemeteries along with data from 38 additional burials from a previously published mid-6th century site6 and analyzed them alongside data from over 550 penecontemporaneous individuals7-19. The range of genetic diversity in all four of these local burial communities is extensive and wider ranging than penecontemporaneous Europeans sequenced to date. Despite many commonalities in burial representation and demography, we find that there were substantial differences in genetic ancestry between the sites. We detect evidence of northern European gene flow into the Lake Balaton region. Additionally, we observe a statistically significant association between dress artefacts and genetic ancestry among 5th century genetically female burials. Our analysis shows that the formation of early Medieval communities was a multifarious process even at a local level, consisting of genetically heterogeneous groups.

genetics↗

bioRxiv2019

Unravelling the genetic architecture of musical rhythm

Moving in synchrony to the beat is a fundamental component of musicality. Here, we conducted a genome-wide association study (GWAS) to identify common genetic variants associated with beat synchronization in 606,825 individuals. Beat synchronization exhibited a highly polygenic architecture, with sixty-nine loci reaching genome-wide significance (p<5x10-8) and SNP-based heritability (on the liability scale) of 13%-16%. Heritability was enriched for genes expressed in brain tissues, and for fetal and adult brain-specific gene regulatory elements, underscoring the role of central nervous system-expressed genes linked to the genetic basis of the trait. We performed validations of the self-report phenotype (through internet-based experiments) and of the GWAS (polygenic scores for beat synchronization were associated with patients algorithmically classified as musicians in medical records of a separate biobank). Genetic correlations with breathing function, motor function, processing speed, and chronotype suggest shared genetic architecture with beat synchronization and provide avenues for new phenotypic and genetic explorations.

genetics↗

bioRxiv2019

Genetic risk for major depressive disorder and loneliness in gender-specific associations with coronary artery disease

ImportanceEpidemiological evidence indicates that major depressive disorder (MDD) and loneliness both reduce life expectancies, but mechanisms underlying the excess morbidity are unclear. Electronic health records (EHRs) linked to genetic data offer new opportunities to address this knowledge gap.\n\nObjectiveTo determine the medical morbidity pattern associated with genetic risk factors for MDD and loneliness, two common psychological traits with adverse health outcomes.\n\nDesignPhenome-wide association study using EHRs spanning 1990 to 2017 from the Vanderbilt University Medical Center biobank, BioVU. Top associations with coronary artery disease (CAD) were replicated in the Atherosclerosis Risk in Communities (ARIC) cohort.\n\nSettingHospital-based EHR study, with replication in a population-based cohort study.\n\nParticipants18,385 genotyped adult patients in BioVU. Replication in ARIC included 7,197 genotyped participants. All participants were of European ancestry.\n\nExposuresPolygenic scores for MDD and loneliness were developed for each individual using previously published meta-GWAS summary statistics.\n\nMain Outcomes and MeasuresThe phenome-wide association study included 882 clinical diagnoses ascertained via billing codes in the EHR. ARIC included 1598 incident CAD cases.\n\nResultsBioVU patients had a median EHR length of 9.91 years. In the phenome-wide association study, polygenic scores for MDD and loneliness were significantly associated with psychiatric and cardiac phenotypes. Targeted analyses of CAD in 3,893 cases and 4,197 controls in BioVU found odds ratios of 1.11 (95% CI, 1.04-1.18; P=8.43x10-4) and 1.13 (95% CI, 1.07-1.20; P=4.51x10-6) per 1-SD increase in the polygenic scores for MDD and loneliness, respectively. Comparable hazard ratios in ARIC were 1.07 (95% CI, 0.99-1.14; P=0.07) and 1.07 (1.01-1.15; P=0.03). Across both studies, the increased risk persisted in women after adjusting for multiple conventional risk factors, a polygenic score for CAD, and psychiatric symptoms (available in BioVU). Controlling for genetic risk factors shared between MDD and loneliness, the polygenic score for loneliness conditioned on MDD remained associated with CAD risk, but the polygenic score for MDD conditioned on loneliness did not.\n\nConclusions and RelevanceGenetic risk factors for MDD and loneliness act pleiotropically to increase CAD risk in women. Continued research into the biological and clinical connections between the heart and mind is warranted.

genetics↗

bioRxiv2018

Penetrance and pleiotropy of polygenic risk scores for schizophrenia in 90,000 patients across three healthcare systems

BACKGROUNDIndividuals at high risk schizophrenia may benefit from early intervention but few validated risk predictors are available. Genetic profiling is one approach to risk stratification that has been extensively validated in research cohorts, but its utility in clinical settings remains largely unexplored. Moreover, the broad health consequences of a high genetic risk of schizophrenia are poorly understood, despite being highly relevant to treatment decisions.\n\nMETHODSWe used electronic health records of 91,980 patients from three large healthcare systems to evaluate the penetrance and pleiotropy of genetic risk for schizophrenia. Polygenic risk scores (PRSs) for schizophrenia were calculated from meta-analysis summary statistics and tested for association with schizophrenia diagnostic codes and 1338 code-defined disease categories in a phenome-wide association study. Effect estimates were meta-analyzed across sites, and follow-up analyses evaluated the effect of a schizophrenia diagnosis.\n\nRESULTSPRSs were robustly associated with schizophrenia (odds ratio per standard deviation increase in PRS = 1.65 [95% confidence interval (CI), 1.5-1.8], p = 1.25 x 10-16) and patients in the highest risk decile of the PRS distribution had a four-fold increased odds of schizophrenia compared to those in the bottom decile (95% CI, 2.4-6.5, p = 4.43 x 10-8). PRSs were also associated with other psychiatric phenotypes, including anxiety disorders, bipolar disorder, depression, substance use disorders, personality disorders, and suicidal behavior. Non-psychiatric associations included heart palpitations, urinary syndromes, obesity, and nonspecific somatic symptoms. Most associations remained significant when conditioning on a diagnosis of schizophrenia, indicating genetic pleiotropy.\n\nCONCLUSIONSWe demonstrate that an available measure of genetic risk for schizophrenia is robustly associated with schizophrenia in healthcare settings and has pleiotropic effects on related psychiatric disorders as well as other medical symptoms and syndromes. Our results provide an initial indication of the opportunities and limitations that may arise with the future application of PRS testing in healthcare systems.

genetics↗