The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Rs671 in the aldehyde dehydrogenase 2 gene (ALDH2) is the cause of Asian alcohol flushing response after drinking. ALDH2 detoxifies endogenous aldehydes, which are the major source of DNA damage repaired by the Fanconi anemia pathway. Here, we show that the rs671 defective allele in combination with mutations in the alcohol dehydrogenase 5 gene, which encodes formaldehyde dehydrogenase (ADH5^FDH), causes a previously unidentified disorder, AMeD (aplastic anemia, mental retardation, and dwarfism) syndrome. Cellular studies revealed that a decrease in the formaldehyde tolerance underlies a loss of differentiation and proliferation capacity of hematopoietic stem cells. Moreover, Adh5^−/−Aldh2^E506K/E506K double-deficient mice recapitulated key clinical features of AMeDS, showing short life span, dwarfism, and hematopoietic failure. Collectively, our results suggest that the combined deficiency of formaldehyde clearance mechanisms leads to the complex clinical features due to overload of formaldehyde-induced DNA damage, thereby saturation of DNA repair processes.

To understand the genetics of steroid-sensitive nephrotic syndrome (SSNS), we conducted a genome-wide association study in 987 childhood SSNS patients and 3,206 healthy controls with Japanese ancestry. Beyond known associations in the HLA-DR/DQ region, common variants in NPHS1-KIRREL2 (rs56117924, P=4.94E-20, odds ratio (OR) =1.90) and TNFSF15 (rs6478109, P=2.54E-8, OR=0.72) regions achieved genome-wide significance and were replicated in Korean, South Asian and African populations. Trans-ethnic meta-analyses including Japanese, Korean, South Asian, African, European, Hispanic and Maghrebian populations confirmed the significant associations of variants in NPHS1-KIRREL2 (Pmeta=6.71E-28, OR=1.88) and TNFSF15 (Pmeta=5.40E-11, OR=1.33) loci. Analysis of the NPHS1 risk alleles with glomerular NPHS1 mRNA expression from the same person revealed allele specific expression with significantly lower expression of the transcript derived from the risk haplotype (Wilcox test p=9.3E-4). Because rare pathogenic variants in NPHS1 cause congenital nephrotic syndrome of the Finnish type (CNSF), the present study provides further evidence that variation along the allele frequency spectrum in the same gene can cause or contribute to both a rare monogenic disease (CNSF) and a more complex, polygenic disease (SSNS).

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 2019 (COVID-19) was announced as an outbreak by the World Health Organization (WHO) in January 2020 and as a pandemic in March 2020. The majority of infected individuals have experienced no or only mild symptoms, ranging from fully asymptomatic cases to mild pneumonic disease. However, a minority of infected individuals develop severe respiratory symptoms. The objective of this study was to identify susceptible HLA alleles and clinical markers that can be used in risk prediction model for the early identification of severe COVID-19 among hospitalized COVID-19 patients. A total of 137 patients with mild COVID-19 (mCOVID-19) and 53 patients with severe COVID-19 (sCOVID-19) were recruited from the Center Hospital of the National Center for Global Health and Medicine (NCGM), Tokyo, Japan for the period of February–August 2020. High-resolution sequencing-based typing for eight HLA genes was performed using next-generation sequencing. In the HLA association studies, HLA-A*11:01:01:01 [P_c = 0.013, OR = 2.26 (1.27–3.91)] and HLA-C*12:02:02:01-HLA-B*52:01:01:02 [P_c = 0.020, OR = 2.25 (1.24–3.92)] were found to be significantly associated with the severity of COVID-19. After multivariate analysis controlling for other confounding factors and comorbidities, HLA-A*11:01:01:01 [P = 3.34E-03, OR = 3.41 (1.50–7.73)], age at diagnosis [P = 1.29E-02, OR = 1.04 (1.01–1.07)] and sex at birth [P = 8.88E-03, OR = 2.92 (1.31–6.54)] remained significant. The area under the curve of the risk prediction model utilizing HLA-A*11:01:01:01, age at diagnosis, and sex at birth was 0.772, with sensitivity of 0.715 and specificity of 0.717. To the best of our knowledge, this is the first article that describes associations of HLA alleles with COVID-19 at the 4-field (highest) resolution level. Early identification of potential sCOVID-19 could help clinicians prioritize medical utility and significantly decrease mortality from COVID-19.

Pediatric steroid-sensitive nephrotic syndrome (pSSNS) is the most common childhood glomerular disease. Previous genome-wide association studies (GWAS) identified a risk locus in the HLA Class II region and three additional independent risk loci. But the genetic architecture of pSSNS, and its genetically driven pathobiology, is largely unknown. Here, we conduct a multi-population GWAS meta-analysis in 38,463 participants (2440 cases). We then conduct conditional analyses and population specific GWAS. We discover twelve significant associations—eight from the multi-population meta-analysis (four novel), two from the multi-population conditional analysis (one novel), and two additional novel loci from the European meta-analysis. Fine-mapping implicates specific amino acid haplotypes in HLA-DQA1 and HLA-DQB1 driving the HLA Class II risk locus. Non-HLA loci colocalize with eQTLs of monocytes and numerous T-cell subsets in independent datasets. Colocalization with kidney eQTLs is lacking but overlap with kidney cell open chromatin suggests an uncharacterized disease mechanism in kidney cells. A polygenic risk score (PRS) associates with earlier disease onset. Altogether, these discoveries expand our knowledge of pSSNS genetic architecture across populations and provide cell-specific insights into its molecular drivers. Evaluating these associations in additional cohorts will refine our understanding of population specificity, heterogeneity, and clinical and molecular associations.