The human genetic epidemiology of COVID-19.

Human genetics can inform the biology and epidemiology of coronavirus disease 2019 (COVID-19) by pinpointing causal mechanisms that explain why some individuals become more severely affected by the disease upon infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Large-scale genetic association studies, encompassing both rare and common genetic variants, have used different study designs and multiple disease phenotype definitions to identify several genomic regions associated with COVID-19. Along with a multitude of follow-up studies, these findings have increased our understanding of disease aetiology and provided routes for management of COVID-19. Important emergent opportunities include the clinical translatability of genetic risk prediction, the repurposing of existing drugs, exploration of variable host effects of different viral strains, study of inter-individual variability in vaccination response and understanding the long-term consequences of SARS-CoV-2 infection. Beyond the current pandemic, these transferrable opportunities are likely to affect the study of many infectious diseases.

Reduced reproductive success is associated with selective constraint on human genes.

Genome-wide sequencing of human populations has revealed substantial variation among genes in the intensity of purifying selection acting on damaging genetic variants1. Although genes under the strongest selective constraint are highly enriched for associations with Mendelian disorders, most of these genes are not associated with disease and therefore the nature of the selection acting on them is not known2. Here we show that genetic variants that damage these genes are associated with markedly reduced reproductive success, primarily owing to increased childlessness, with a stronger effect in males than in females. We present evidence that increased childlessness is probably mediated by genetically associated cognitive and behavioural traits, which may mean that male carriers are less likely to find reproductive partners. This reduction in reproductive success may account for 20% of purifying selection against heterozygous variants that ablate protein-coding genes. Although this genetic association may only account for a very minor fraction of the overall likelihood of being childless (less than 1%), especially when compared to more influential sociodemographic factors, it may influence how genes evolve over time.

Common genetic variants contribute to risk of rare severe neurodevelopmental disorders.

There are thousands of rare human disorders that are caused by single deleterious, protein-coding genetic variants1. However, patients with the same genetic defect can have different clinical presentations2-4, and some individuals who carry known disease-causing variants can appear unaffected5. Here, to understand what explains these differences, we study a cohort of 6,987 children assessed by clinical geneticists to have severe neurodevelopmental disorders such as global developmental delay and autism, often in combination with abnormalities of other organ systems. Although the genetic causes of these neurodevelopmental disorders are expected to be almost entirely monogenic, we show that 7.7% of variance in risk is attributable to inherited common genetic variation. We replicated this genome-wide common variant burden by showing, in an independent sample of 728 trios (comprising a child plus both parents) from the same cohort, that this burden is over-transmitted from parents to children with neurodevelopmental disorders. Our common-variant signal is significantly positively correlated with genetic predisposition to lower educational attainment, decreased intelligence and risk of schizophrenia. We found that common-variant risk was not significantly different between individuals with and without a known protein-coding diagnostic variant, which suggests that common-variant risk affects patients both with and without a monogenic diagnosis. In addition, previously published common-variant scores for autism, height, birth weight and intracranial volume were all correlated with these traits within our cohort, which suggests that phenotypic expression in individuals with monogenic disorders is affected by the same variants as in the general population. Our results demonstrate that common genetic variation affects both overall risk and clinical presentation in neurodevelopmental disorders that are typically considered to be monogenic.

Genetic Architecture of Ischaemic Strokes after COVID-19 Shows Similarities with Large Vessel Strokes.

We aimed to analyse whether patients with ischaemic stroke (IS) occurring within eight days after the onset of COVID-19 (IS-COV) are associated with a specific aetiology of IS. We used SUPERGNOVA to identify genome regions that correlate between the IS-COV cohort (73 IS-COV cases vs. 701 population controls) and different aetiological subtypes. Polygenic risk scores (PRSs) for each subtype were generated and tested in the IS-COV cohort using PRSice-2 and PLINK to find genetic associations. Both analyses used the IS-COV cohort and GWAS from MEGASTROKE (67,162 stroke patients vs. 454,450 population controls), GIGASTROKE (110,182 vs. 1,503,898), and the NINDS Stroke Genetics Network (16,851 vs. 32,473). Three genomic regions were associated (p-value < 0.05) with large artery atherosclerosis (LAA) and cardioembolic stroke (CES). We found four loci targeting the genes PITX2 (rs10033464, IS-COV beta = 0.04, p-value = 2.3 × 10-2, se = 0.02), previously associated with CES, HS6ST1 (rs4662630, IS-COV beta = -0.04, p-value = 1.3 × 10-3, se = 0.01), TMEM132E (rs12941838 IS-COV beta = 0.05, p-value = 3.6 × 10-4, se = 0.01), and RFFL (rs797989 IS-COV beta = 0.03, p-value = 1.0 × 10-2, se = 0.01). A statistically significant PRS was observed for LAA. Our results suggest that IS-COV cases are genetically similar to LAA and CES subtypes. Larger cohorts are needed to assess if the genetic factors in IS-COV cases are shared with the general population or specific to viral infection.

Prevalence and correlates of vitamin D deficiency in adults after traumatic brain injury.

OBJECTIVES: Traumatic brain injury (TBI) is a major cause of long-term disability with variable recovery. Preclinical studies suggest that vitamin D status influences the recovery after TBI. However, there is no published clinical data on links between vitamin D status and TBI outcomes. The aim was to determine the (i) prevalence of vitamin D deficiency/insufficiency, and associations of vitamin D status with (ii) demographic factors and TBI severity, and with (iii) cognitive function, symptoms and quality of life, in adults after TBI. DESIGN: Retrospective audit of patients seen between July 2009 and March 2015. Serum vitamin D (25-hydroxy-cholecalciferol) was categorized as deficient (<40 nmol/l), insufficient (40-70 nmol/l) or replete (>70 nmol/l). PATIENTS: A total of 353 adults seen in tertiary hospital clinic (75·4% lighter skinned, 74·8% male, age median 35·1 year, range 26·6-48·3 year), 0·3-56·5 months after TBI (74·5% moderate-severe). MEASUREMENTS: Serum vitamin D concentrations; Addenbrooke's Cognitive Examination (ACE-R), Beck Depression Inventory-II (BDI-II), SF-36 Quality of Life, Pittsburgh Sleep Quality Index. RESULTS: In total, 46·5% of patients after TBI had vitamin D deficiency and 80·2% insufficiency/deficiency. Patients with vitamin D deficiency had lower ACE-R scores than those of vitamin D replete (mean effect size ± SEM 4·5 ± 2·1, P = 0·034), and higher BDI-II scores than those of vitamin D insufficient (4·5 ± 1·6, P = 0·003), correcting for age, gender, time since TBI and TBI severity. There was no association between vitamin D status and markers of TBI severity, sleep or quality of life. CONCLUSION: Vitamin D deficiency is common in patients after TBI and associated with impaired cognitive function and more severe depressive symptoms.

Recontacting biobank participants to collect lifestyle, behavioural and cognitive information via online questionnaires: lessons from a pilot study within FinnGen.

OBJECTIVES: To recontact biobank participants and collect cognitive, behavioural and lifestyle information via a secure online platform. DESIGN: Biobank-based recontacting pilot study. SETTING: Three Finnish biobanks (Helsinki, Auria, Tampere) recruiting participants from February 2021 to July 2021. PARTICIPANTS: All eligible invitees were enrolled in FinnGen by their biobanks (Helsinki, Auria, Tampere), had available genetic data and were >18 years old. Individuals with severe neuropsychiatric disease or cognitive or physical disabilities were excluded. Lastly, 5995 participants were selected based on their polygenic score for cognitive abilities and invited to the study. Among invitees, 1115 had successfully participated and completed the study questionnaire(s). OUTCOME MEASURES: The primary outcome was the participation rate among study invitees. Secondary outcomes included questionnaire completion rate, quality of data collected and comparison of participation rate boosting strategies. RESULTS: The overall participation rate was 18.6% among all invitees and 23.1% among individuals aged 18-69. A second reminder letter yielded an additional 9.7% participation rate in those who did not respond to the first invitation. Recontacting participants via an online healthcare portal yielded lower participation than recontacting via physical letter. The completion rate of the questionnaire and cognitive tests was high (92% and 85%, respectively), and measurements were overall reliable among participants. For example, the correlation (r) between self-reported body mass index and that collected by the biobanks was 0.92. CONCLUSION: In summary, this pilot suggests that recontacting FinnGen participants with the goal to collect a wide range of cognitive, behavioural and lifestyle information without additional engagement results in a low participation rate, but with reliable data. We suggest that such information be collected at enrolment, if possible, rather than via post hoc recontacting.

The contribution of X-linked coding variation to severe developmental disorders.

Over 130 X-linked genes have been robustly associated with developmental disorders, and X-linked causes have been hypothesised to underlie the higher developmental disorder rates in males. Here, we evaluate the burden of X-linked coding variation in 11,044 developmental disorder patients, and find a similar rate of X-linked causes in males and females (6.0% and 6.9%, respectively), indicating that such variants do not account for the 1.4-fold male bias. We develop an improved strategy to detect X-linked developmental disorders and identify 23 significant genes, all of which were previously known, consistent with our inference that the vast majority of the X-linked burden is in known developmental disorder-associated genes. Importantly, we estimate that, in male probands, only 13% of inherited rare missense variants in known developmental disorder-associated genes are likely to be pathogenic. Our results demonstrate that statistical analysis of large datasets can refine our understanding of modes of inheritance for individual X-linked disorders.