The landscape of genomic structural variation in Indigenous Australians.

Indigenous Australians harbour rich and unique genomic diversity. However, Aboriginal and Torres Strait Islander ancestries are historically under-represented in genomics research and almost completely missing from reference datasets1-3. Addressing this representation gap is critical, both to advance our understanding of global human genomic diversity and as a prerequisite for ensuring equitable outcomes in genomic medicine. Here we apply population-scale whole-genome long-read sequencing4 to profile genomic structural variation across four remote Indigenous communities. We uncover an abundance of large insertion-deletion variants (20-49 bp; n = 136,797), structural variants (50 b-50 kb; n = 159,912) and regions of variable copy number (>50 kb; n = 156). The majority of variants are composed of tandem repeat or interspersed mobile element sequences (up to 90%) and have not been previously annotated (up to 62%). A large fraction of structural variants appear to be exclusive to Indigenous Australians (12% lower-bound estimate) and most of these are found in only a single community, underscoring the need for broad and deep sampling to achieve a comprehensive catalogue of genomic structural variation across the Australian continent. Finally, we explore short tandem repeats throughout the genome to characterize allelic diversity at 50 known disease loci5, uncover hundreds of novel repeat expansion sites within protein-coding genes, and identify unique patterns of diversity and constraint among short tandem repeat sequences. Our study sheds new light on the dimensions and dynamics of genomic structural variation within and beyond Australia.

Indigenous Australian genomes show deep structure and rich novel variation.

The Indigenous peoples of Australia have a rich linguistic and cultural history. How this relates to genetic diversity remains largely unknown because of their limited engagement with genomic studies. Here we analyse the genomes of 159 individuals from four remote Indigenous communities, including people who speak a language (Tiwi) not from the most widespread family (Pama-Nyungan). This large collection of Indigenous Australian genomes was made possible by careful community engagement and consultation. We observe exceptionally strong population structure across Australia, driven by divergence times between communities of 26,000-35,000 years ago and long-term low but stable effective population sizes. This demographic history, including early divergence from Papua New Guinean (47,000 years ago) and Eurasian groups1, has generated the highest proportion of previously undescribed genetic variation seen outside Africa and the most extended homozygosity compared with global samples. A substantial proportion of this variation is not observed in global reference panels or clinical datasets, and variation with predicted functional consequence is more likely to be homozygous than in other populations, with consequent implications for medical genomics2. Our results show that Indigenous Australians are not a single homogeneous genetic group and their genetic relationship with the peoples of New Guinea is not uniform. These patterns imply that the full breadth of Indigenous Australian genetic diversity remains uncharacterized, potentially limiting genomic medicine and equitable healthcare for Indigenous Australians.

A globally diverse reference alignment and panel for imputation of mitochondrial DNA variants.

BACKGROUND: Variation in mitochondrial DNA (mtDNA) identified by genotyping microarrays or by sequencing only the hypervariable regions of the genome may be insufficient to reliably assign mitochondrial genomes to phylogenetic lineages or haplogroups. This lack of resolution can limit functional and clinical interpretation of a substantial body of existing mtDNA data. To address this limitation, we developed and evaluated a large, curated reference alignment of complete mtDNA sequences as part of a pipeline for imputing missing mtDNA single nucleotide variants (mtSNVs). We call our reference alignment and pipeline MitoImpute. RESULTS: We aligned the sequences of 36,960 complete human mitochondrial genomes downloaded from GenBank, filtered and controlled for quality. These sequences were reformatted for use in imputation software, IMPUTE2. We assessed the imputation accuracy of MitoImpute by measuring haplogroup and genotype concordance in data from the 1000 Genomes Project and the Alzheimer's Disease Neuroimaging Initiative (ADNI). The mean improvement of haplogroup assignment in the 1000 Genomes samples was 42.7% (Matthew's correlation coefficient = 0.64). In the ADNI cohort, we imputed missing single nucleotide variants. CONCLUSION: These results show that our reference alignment and panel can be used to impute missing mtSNVs in existing data obtained from using microarrays, thereby broadening the scope of functional and clinical investigation of mtDNA. This improvement may be particularly useful in studies where participants have been recruited over time and mtDNA data obtained using different methods, enabling better integration of early data collected using less accurate methods with more recent sequence data.

Mitochondrial pathway polygenic risk scores are associated with Alzheimer's Disease.

Genetic, animal and epidemiological studies involving biomolecular and clinical endophenotypes implicate mitochondrial dysfunction in Alzheimer's disease (AD) pathogenesis. Polygenic risk scores (PRS) provide a novel approach to assess biological pathway-associated disease risk by combining the effects of variation at multiple, functionally related genes. We investigated the associations of PRS for genes involved in 12 mitochondrial pathways (pathway-PRS) with AD in 854 participants from Alzheimer's Disease Neuroimaging Initiative. Pathway-PRS for the nuclear-encoded mitochondrial genome (OR: 1.99 [95% Cl: 1.70, 2.35]) and three mitochondrial pathways is significantly associated with increased AD risk: (i) response to oxidative stress (OR: 2.01 [95% Cl: 1.71, 2.38]); (ii) mitochondrial transport (OR: 1.81 [95% Cl: 1.55, 2.13]); (iii) hallmark oxidative phosphorylation (OR: 1.22 [95% Cl: 1.06, 1.40]. Therapeutic approaches targeting these pathways may have the potential for modifying AD pathogenesis. Further investigation is required to establish a causal role for these pathways in AD pathology.

Beyond platitudes: a qualitative study of Australian Aboriginal people's perspectives on biobanking.

BACKGROUND: Biobanks are vital resources for genetics and genomics, and it is broadly recognised that for maximal benefit it is essential that they include samples and data from diverse ancestral groups. The inclusion of First Nations people, in particular, is important to prevent biobanking research from exacerbating existing health inequities, and to ensure that these communities share in the benefits arising from research. AIMS: To explore the perspectives of Australian Aboriginal people whose tissue - or that of their family members - has been stored in the biobank of the National Centre for Indigenous Genomics (NCIG). METHODS: Semi-structured interviews with 42 Aboriginal people from the Titjikala, Galiwinku, Tiwi Islands, Yarrabah, Fitzroy Crossing, Derby, One Arm Point and Mulan communities, as well as a formal discussion with A. Hermes, an Indigenous Community Engagement Coordinator at the NCIG who had conducted the interviews. The interviews and the structured discussion were double coded using a procedure informed by Charmaz's outline of grounded theory analysis and Morse's outline of the cognitive basis of qualitative research. RESULTS: In this article, we report on A. Hermes' interviews with members from the above Aboriginal communities, as well as on her personal views, experiences, and interpretations of the interviews she conducted with other community members. We found that participation in the NCIG biobank raised issues around broken trust, grief and loss, but also - somewhat unexpectedly - was perceived as a source of empowerment, hope and reconnection. CONCLUSIONS: This research reminds us (again) of the need to engage deeply with communities in order to respond appropriately with respect for their cultural values and norms, and to develop culturally relevant policies and processes that enhance the benefits of biobank participation and minimise potential harms.

PACIFIC: a lightweight deep-learning classifier of SARS-CoV-2 and co-infecting RNA viruses.

Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severity. However, there is currently no dedicated method to identify viral co-infections in patient RNA-seq data. We developed PACIFIC, a deep-learning algorithm that accurately detects SARS-CoV-2 and other common RNA respiratory viruses from RNA-seq data. Using in silico data, PACIFIC recovers the presence and relative concentrations of viruses with > 99% precision and recall. PACIFIC accurately detects SARS-CoV-2 and other viral infections in 63 independent in vitro cell culture and patient datasets. PACIFIC is an end-to-end tool that enables the systematic monitoring of viral infections in the current global pandemic.

Barriers and Considerations for Diagnosing Rare Diseases in Indigenous Populations.

Advances in omics and specifically genomic technologies are increasingly transforming rare disease diagnosis. However, the benefits of these advances are disproportionately experienced within and between populations, with Indigenous populations frequently experiencing diagnostic and therapeutic inequities. The International Rare Disease Research Consortium (IRDiRC) multi-stakeholder partnership has been advancing toward the vision of all people living with a rare disease receiving an accurate diagnosis, care, and available therapy within 1 year of coming to medical attention. In order to further progress toward this vision, IRDiRC has created a taskforce to explore the access barriers to diagnosis of rare genetic diseases faced by Indigenous peoples, with a view of developing recommendations to overcome them. Herein, we provide an overview of the state of play of current barriers and considerations identified by the taskforce, to further stimulate awareness of these issues and the passage toward solutions. We focus on analyzing barriers to accessing genetic services, participating in genomic research, and other aspects such as concerns about data sharing, the handling of biospecimens, and the importance of capacity building.

Equitable Expanded Carrier Screening Needs Indigenous Clinical and Population Genomic Data.

Expanded carrier screening (ECS) for recessive monogenic diseases requires prior knowledge of genomic variation, including DNA variants that cause disease. The composition of pathogenic variants differs greatly among human populations, but historically, research about monogenic diseases has focused mainly on people with European ancestry. By comparison, less is known about pathogenic DNA variants in people from other parts of the world. Consequently, inclusion of currently underrepresented Indigenous and other minority population groups in genomic research is essential to enable equitable outcomes in ECS and other areas of genomic medicine. Here, we discuss this issue in relation to the implementation of ECS in Australia, which is currently being evaluated as part of the national Government's Genomics Health Futures Mission. We argue that significant effort is required to build an evidence base and genomic reference data so that ECS can bring significant clinical benefit for many Aboriginal and/or Torres Strait Islander Australians. These efforts are essential steps to achieving the Australian Government's objectives and its commitment "to leveraging the benefits of genomics in the health system for all Australians." They require culturally safe, community-led research and community involvement embedded within national health and medical genomics programs to ensure that new knowledge is integrated into medicine and health services in ways that address the specific and articulated cultural and health needs of Indigenous people. Until this occurs, people who do not have European ancestry are at risk of being, in relative terms, further disadvantaged.

APOE ε4 and the Influence of Sex, Age, Vascular Risk Factors, and Ethnicity on Cognitive Decline.

We aimed to examine the relationship between Apolipoprotein E ε4 (APOE*4) carriage on cognitive decline, and whether these associations were moderated by sex, baseline age, ethnicity, and vascular risk factors. Participants were 19,225 individuals aged 54-103 years from 15 longitudinal cohort studies with a mean follow-up duration ranging between 1.2 and 10.7 years. Two-step individual participant data meta-analysis was used to pool results of study-wise analyses predicting memory and general cognitive decline from carriage of one or two APOE*4 alleles, and moderation of these associations by age, sex, vascular risk factors, and ethnicity. Separate pooled estimates were calculated in both men and women who were younger (ie, 62 years) and older (ie, 80 years) at baseline. Results showed that APOE*4 carriage was related to faster general cognitive decline in women, and faster memory decline in men. A stronger dose-dependent effect was observed in older men, with faster general cognitive and memory decline in those carrying two versus one APOE*4 allele. Vascular risk factors were related to an increased effect of APOE*4 on memory decline in younger women, but a weaker effect of APOE*4 on general cognitive decline in older men. The relationship between APOE*4 carriage and memory decline was larger in older-aged Asians than Whites. In sum, APOE*4 is related to cognitive decline in men and women, although these effects are enhanced by age and carriage of two APOE*4 alleles in men, a higher numbers of vascular risk factors during the early stages of late adulthood in women, and Asian ethnicity.

ADGRL3 (LPHN3) variants predict substance use disorder.

Genetic factors are strongly implicated in the susceptibility to develop externalizing syndromes such as attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, and substance use disorder (SUD). Variants in the ADGRL3 (LPHN3) gene predispose to ADHD and predict ADHD severity, disruptive behaviors comorbidity, long-term outcome, and response to treatment. In this study, we investigated whether variants within ADGRL3 are associated with SUD, a disorder that is frequently co-morbid with ADHD. Using family-based, case-control, and longitudinal samples from disparate regions of the world (n = 2698), recruited either for clinical, genetic epidemiological or pharmacogenomic studies of ADHD, we assembled recursive-partitioning frameworks (classification tree analyses) with clinical, demographic, and ADGRL3 genetic information to predict SUD susceptibility. Our results indicate that SUD can be efficiently and robustly predicted in ADHD participants. The genetic models used remained highly efficient in predicting SUD in a large sample of individuals with severe SUD from a psychiatric institution that were not ascertained on the basis of ADHD diagnosis, thus identifying ADGRL3 as a risk gene for SUD. Recursive-partitioning analyses revealed that rs4860437 was the predominant predictive variant. This new methodological approach offers novel insights into higher order predictive interactions and offers a unique opportunity for translational application in the clinical assessment of patients at high risk for SUD.

Targeting Neuroplasticity, Cardiovascular, and Cognitive-Associated Genomic Variants in Familial Alzheimer's Disease.

The identification of novel genetic variants contributing to the widespread in the age of onset (AOO) of Alzheimer's disease (AD) could aid in the prognosis and/or development of new therapeutic strategies focused on early interventions. We recruited 78 individuals with AD from the Paisa genetic isolate in Antioquia, Colombia. These individuals belong to the world largest multigenerational and extended pedigree segregating AD as a consequence of a dominant fully penetrant mutation in the PSEN1 gene and exhibit an AOO ranging from the early 1930s to the late 1970s. To shed light on the genetic underpinning that could explain the large spread of the age of onset (AOO) of AD, 64 single nucleotide polymorphisms (SNP) associated with neuroanatomical, cardiovascular, and cognitive measures in AD were genotyped. Standard quality control and filtering procedures were applied, and single- and multi-locus linear mixed-effects models were used to identify AOO-associated SNPs. A full two-locus interaction model was fitted to define how identified SNPs interact to modulate AOO. We identified two key epistatic interactions between the APOE*E2 allele and SNPs ASTN2-rs7852878 and SNTG1-rs16914781 that delay AOO by up to ~ 8 years (95% CI 3.2-12.7, P = 1.83 × 10-3) and ~ 7.6 years (95% CI 3.3-11.8, P = 8.69 × 10-4), respectively, and validated our previous finding indicating that APOE*E2 delays AOO of AD in PSEN1 E280 mutation carriers. This new evidence involving APOE*E2 as an AOO delayer could be used for developing precision medicine approaches and predictive genomics models to potentially determine AOO in individuals genetically predisposed to AD.

Indigenous Genetics and Rare Diseases: Harmony, Diversity and Equity.

Advances in our understanding of genetic and rare diseases are changing the face of healthcare. Crucially, the global community must implement these advances equitably to reduce health disparities, including between Indigenous and non-Indigenous peoples. We take an Australian perspective to illustrate some key areas that are fundamental to the equitable translation of new knowledge for the improved diagnosis of genetic and rare diseases for Indigenous people. Specifically, we focus on inequalities in access to clinical genetics services and the lack of genetic and phenomic reference data to inform diagnoses. We provide examples of ways in which these inequities are being addressed through Australian partnerships to support a harmonious and inclusive approach to ensure that benefits from traditional wisdom, community knowledge and shared experiences are interwoven to support and inform implementation of new knowledge from genomics and precision public health. This will serve to deliver benefits to all of our diverse citizens, including Indigenous populations.

Validating the role of the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI) and a genetic risk score in progression to cognitive impairment in a population-based cohort of older adults followed for 12 years.

BACKGROUND: The number of people living with dementia is expected to exceed 130 million by 2050, which will have serious personal, social and economic implications. Employing successful intervention and treatment strategies focused on disease prevention is currently the only available approach that can have an impact on the projected rates of dementia, with risk assessment being a key component of population-based risk reduction for identification of at-risk individuals. We evaluated a risk index comprising lifestyle, medical and demographic factors (the Australian National University Alzheimer's Disease Risk Index [ANU-ADRI]), as well as a genetic risk score (GRS), for assessment of the risk of progression to mild cognitive impairment (MCI). METHODS: The ANU-ADRI was computed for the baseline assessment of 2078 participants in the Personality and Total Health (PATH) Through Life project. GRSs were constructed on the basis of 25 single-nucleotide polymorphisms previously associated with Alzheimer's disease (AD). Participants were assessed for clinically diagnosed MCI and dementia as well as psychometric test-based MCI (MCI-TB) at 12 years of follow-up. Multi-state models were used to estimate the odds of transitioning from cognitively normal (CN) to MCI, dementia and MCI-TB over 12 years according to baseline ANU-ADRI and GRS. RESULTS: A higher ANU-ADRI score was associated with increased risk of progressing from CN to both MCI and MCI-TB (HR 1.07 [95% CI 1.04-1.11]; 1.07 [1.04-1.09]). The GRS was associated with transitions from CN to dementia (HR 4.19 [95% CI 1.72-10.20), but not to MCI or MCI-TB (HR 1.05 [95% CI 0.86-1.29]; 1.03 [0.87-1.21]). Limitations of our study include that the ethnicity of participants in the PATH project is predominately Caucasian, potentially limiting the generalisability of the results of this study to people of other ethnicities. Biomarkers of AD were not available to define MCI attributable to AD. Not all the predictive variables for the ANU-ADRI were available in the PATH project. CONCLUSIONS: In the general population, the ANU-ADRI, comprising lifestyle, medical and demographic factors, is associated with the risk of progression from CN to MCI, whereas a GRS comprising the main AD risk genes was not associated with this risk. The ANU-ADRI may be used for population-level risk assessment and screening.

Late Onset Alzheimer's Disease Risk Variants in Cognitive Decline: The PATH Through Life Study.

Recent genome wide association studies have identified a number of single nucleotide polymorphisms associated with late onset Alzheimer's disease (LOAD). We examined the associations of 24 LOAD risk loci, individually and collectively as a genetic risk score, with cognitive function. We used data from 1,626 non-demented older Australians of European ancestry who were examined up to four times over 12 years on tests assessing episodic memory, working memory, vocabulary, and information processing speed. Linear mixed models were generated to examine associations between genetic factors and cognitive performance. Twelve SNPs were significantly associated with baseline cognitive performance (ABCA7, MS4A4E, SORL1), linear rate of change (APOE, ABCA7, INPP5D, ZCWPW1, CELF1), or quadratic rate of change (APOE, CLU, EPHA1, HLA-DRB5, INPP5D, FERMT2). In addition, a weighted genetic risk score was associated with linear rate of change in episodic memory and information processing speed. Our results suggest that a minority of AD related SNPs may be associated with non-clinical cognitive decline. Further research is required to verify these results and to examine the effect of preclinical AD in genetic association studies of cognitive decline. The identification of LOAD risk loci associated with non-clinical cognitive performance may help in screening for individuals at greater risk of cognitive decline.

Regional Brain Volumes and ADHD Symptoms in Middle-Aged Adults: The PATH Through Life Study.

OBJECTIVE: We investigated whether volumetric differences in ADHD-associated brain regions are related to current symptoms of inattention and hyperactivity in healthy middle-aged adults and whether co-occurring anxiety/depression symptoms moderate these relationships. METHOD: ADHD Self-Report Scale and Brief Patient Health Questionnaire were used to assess current symptoms of inattention, hyperactivity, anxiety, and depression in a population-based sample ( n = 269). Brain volumes, measured using a semi-automated method, were analyzed using multiple regression and structural equation modeling to evaluate brain volume-inattention/hyperactivity symptom relationships for selected regions. RESULTS: Volumes of the left nucleus accumbens and a region overlapping the dorsolateral prefrontal cortex were positively associated with inattention symptoms. Left hippocampal volume was negatively associated with hyperactivity symptoms. The brain volume-inattention/hyperactivity symptom associations were stronger when anxiety/depression symptoms were controlled for. CONCLUSION: Inattention and hyperactivity symptoms in middle-aged adults are associated with different brain regions and co-occurring anxiety/depression symptoms moderate these brain-behavior relationships.

The dynamic upper limit of human lifespan.

We respond to claims by Dong et al. that human lifespan is limited below 125 years. Using the log-linear increase in mortality rates with age to predict the upper limits of human survival we find, in contrast to Dong et al., that the limit to human lifespan is historically flexible and increasing. This discrepancy can be explained by Dong et al.'s use of data with variable sample sizes, age-biased rounding errors, and log(0) instead of log(1) values in linear regressions. Addressing these issues eliminates the proposed 125-year upper limit to human lifespan.

Reproductive success is predicted by social dynamics and kinship in managed animal populations.

Kin and group interactions are important determinants of reproductive success in many species. Their optimization could, therefore, potentially improve the productivity and breeding success of managed populations used for agricultural and conservation purposes. Here we demonstrate this potential using a novel approach to measure and predict the effect of kin and group dynamics on reproductive output in a well-known species, the meerkat Suricata suricatta. Variation in social dynamics predicts 30% of the individual variation in reproductive success of this species in managed populations, and accurately forecasts reproductive output at least two years into the future. Optimization of social dynamics in captive meerkat populations doubles their projected reproductive output. These results demonstrate the utility of a quantitative approach to breeding programs informed by social and kinship dynamics. They suggest that this approach has great potential for improvements in the management of social endangered and agricultural species.