An integrated strategy to identify COVID‐19 causal genes and characteristics represented by LRRC37A2

Zhu, Zijun; Chen, Xinyu; Wang, Chao; Zhang, Sainan; Yu, Rui; Xie, Yubin; Ong, Chon Phin; Cheng, Liang; Shi, Lei; Zhang, Xue

doi:10.1002/jmv.28585

Cited by 3 publications

(4 citation statements)

References 88 publications

(124 reference statements)

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“…Each country/state/area has its own unique mix of risk factors for COVID-19-related deaths at each age, such as the proportion of the population in high-exposure occupations, those with obesity or other clinical risk factors, including genetic factors, the risk of transmission due to city/rural living, or risk-taking behavior, etc. [19][20][21][47][48][49][50][59][60][61][62][63][64][65][66][67][68][69][70][71]. This is illustrated in Figure 6, which uses data from the USA rather than England and Wales and includes both males and females.…”

Section: Modification Of the Age Profile In Different Countries/state...mentioning

confidence: 99%

COVID-19-Related Age Profiles for SARS-CoV-2 Variants in England and Wales and States of the USA (2020 to 2022): Impact on All-Cause Mortality

Jones,

Ponomarenko

2023

Infectious Disease Reports

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Since 2020, COVID-19 has caused serious mortality around the world. Given the ambiguity in establishing COVID-19 as the direct cause of death, we first investigate the effects of age and sex on all-cause mortality during 2020 and 2021 in England and Wales. Since infectious agents have their own unique age profile for death, we use a 9-year time series and several different methods to adjust single-year-of-age deaths in England and Wales during 2019 (the pre-COVID-19 base year) to a pathogen-neutral single-year-of-age baseline. This adjusted base year is then used to confirm the widely reported higher deaths in males for most ages above 43 in both 2020 and 2021. During 2020 (+COVID-19 but no vaccination), both male and female population-adjusted deaths significantly increased above age 35. A significant reduction in all-cause mortality among both males and females aged 75+ could be demonstrated in 2021 during the widespread COVID-19 vaccination period; however, deaths below age 75 progressively increased. This finding arises from a mix of vaccination coverage and year-of-age profiles of deaths for the different SARS-CoV-2 variants. In addition, specific effects of age around puberty were demonstrated, where females had higher deaths than males. There is evidence that year-of-birth cohorts may also be involved, indicating that immune priming to specific pathogen outbreaks in the past may have led to lower deaths for some birth cohorts. To specifically identify the age profile for the COVID-19 variants from 2020 to 2023, we employ the proportion of total deaths at each age that are potentially due to or ‘with’ COVID-19. The original Wuhan strain and the Alpha variant show somewhat limited divergence in the age profile, with the Alpha variant shifting to a moderately higher proportion of deaths below age 84. The Delta variant specifically targeted individuals below age 65. The Omicron variants showed a significantly lower proportion of overall mortality, with a markedly higher relative proportion of deaths above age 65, steeply increasing with age to a maximum around 100 years of age. A similar age profile for the variants can be seen in the age-banded deaths in US states, although they are slightly obscured by using age bands rather than single years of age. However, the US data shows that higher male deaths are greatly dependent on age and the COVID variant. Deaths assessed to be ‘due to’ COVID-19 (as opposed to ‘involving’ COVID-19) in England and Wales were especially overestimated in 2021 relative to the change in all-cause mortality. This arose as a by-product of an increase in COVID-19 testing capacity in late 2020. Potential structure–function mechanisms for the age-specificity of SARS-CoV-2 variants are discussed, along with potential roles for small noncoding RNAs (miRNAs). Using data from England, it is possible to show that the unvaccinated do indeed have a unique age profile for death from each variant and that vaccination alters the shape of the age profile in a manner dependent on age, sex, and the variant. The question is posed as to whether vaccines based on different variants carry a specific age profile.

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Section: Modification Of the Age Profile In Different Countries/state...mentioning

confidence: 99%

COVID-19-Related Age Profiles for SARS-CoV-2 Variants in England and Wales and States of the USA (2020 to 2022): Impact on All-Cause Mortality

Jones,

Ponomarenko

2023

Infectious Disease Reports

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“…The results of coloc can be found in Table S2 and coloc-SuSiE in Table S3. In the four analyzed tissues, we identified a total of 28 unique genes (Figure S2), among these genes, 50% (14/28) have been reported to be associated with COVID-19 ( DPP9 30,31 , WNT3 32,33 , ABO 34,35 , NAPSA , 36 GSDMB 37,38 , RAB2A 29 , OAS1 39 , OAS3 7 , LRRC37A2 40 , MAPT 32 , FUT2 41,42 , IKZF3 43 , ICAM5 41,44 , CCR9 34,45 ).…”

Section: Resultsmentioning

confidence: 99%

“…In the four analyzed tissues, we identified a total of 28 unique genes post coloc/coloc-SuSiE (Figure S2), among these genes, 50% (14/28) have been reported to be associated with COVID-19 ( DPP9 31,32 , WNT3 33,34 , ABO 35,36 , NAPSA , 37 GSDMB 38,39 , RAB2A 30 , OAS1 40 , OAS3 5 , LRRC37A2 41 , MAPT 33 , FUT2 42,43 , IKZF3 44 , ICAM5 42,45 , CCR9 35,46 ). CCR9 and MAPT are druggable genes.…”

Section: Resultsmentioning

confidence: 99%

Integrating population-level and cell-based signatures for drug repositioning

He,

Xu,

Zhou

et al. 2023

Preprint

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Drug repositioning presents a streamlined and cost-efficient way to expand the range of therapeutic possibilities. Furthermore, drugs with genetic evidence are more likely to progress successfully through clinical trials towards FDA approval. Exploiting these developments, single gene-based drug repositioning methods have been implemented, but approaches leveraging the entire spectrum of molecular signatures are critically underexplored. Most multi-gene-based approaches rely on differential gene expression (DGE) analysis, which is prone to identify the molecular consequence of disease and renders causal inference challenging. We propose a framework TReD (Transcriptome-informed Reversal Distance) that integrates population-level disease signatures robust to reverse causality and cell-based drug-induced transcriptome response profiles. TReD embeds the disease signature and drug profile in a high-dimensional normed space, quantifying the reversal potential of candidate drugs in a disease-related cell screen assay. The robustness is ensured by evaluation in additional cell screens. For an application, we implement the framework to identify potential drugs against COVID-19. Taking transcriptome-wide association study (TWAS) results from four relevant tissues and three DGE results as disease features, we identify 37 drugs showing potential reversal roles in at least four of the seven disease signatures. Notably, over 70% (27/37) of the drugs have been linked to COVID-19 from other studies, and among them, eight drugs are supported by ongoing/completed clinical trials. For example, TReD identifies the well-studied JAK1/JAK2 inhibitor baricitinib, the first FDA-approved immunomodulatory treatment for COVID-19. Novel potential candidates, including enzastaurin, a selective inhibitor of PKC-beta which can be activated by SARS-CoV-2, are also identified. In summary, we propose a comprehensive genetics-anchored framework integrating population-level signatures and cell-based screens that can accelerate the search for new therapeutic strategies.

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“…Hence proportion of the population in high exposure occupations, with obesity and other clinical risk factors including genetic factors, risk of transmission due to city/rural or risk-taking behavior, etc. [19][20][21][47][48][49][50][59][60][61][62][63][64][65][66][67][68][69][70][71]. This is illustrated in Figure 6 using data from the USA rather than England and Wales and includes both males and females.…”

Section: Modification Of the Age Profile In Different Countries/state...mentioning

confidence: 99%

Age Profiles for SARS-CoV-2 Variants in England and Wales and States of the USA (2020 to 2022): Impact on All-Cause Mor-Tality

Jones¹,

Ponomarenko²

2023

Preprint

View full text Add to dashboard Cite

Since 2020 COVID-19 has caused serious mortality around the world. Given the ambiguity in es-tablishing COVID-19 as the direct cause of death we first investigate the effects of age and sex upon all-cause mortality during 2020 and 2021 in England and Wales. Since infectious agents have their own unique age profile for death, we explore several methods to adjust single year of age deaths in England and Wales during 2019 (the pre-COVID-19 base year) to a pathogen-neutral single year of age baseline. This adjusted base year is then used to confirm the widely reported higher deaths in males for most ages above 43 years in both 2020 and 2021. During 2020 (+ COVID-19 but no vac-cination) both male and female population-adjusted deaths were significantly increased above age 35. A significant reduction in all-cause mortality among both males and females aged 75+ could be demonstrated in 2021 during widespread COVID–19 vaccination, however, below age 75 deaths progressively increased. This finding arises from a mix of vaccination and year of age profiles of deaths for the different SARS-CoV-2 variants. In addition, specific effects for age around puberty were demonstrated where females had higher deaths rather than males. There is evidence that year-of-birth cohorts may also be involved, indicating that immune priming to specific pathogen outbreaks in the past may lead to lower deaths for some birth cohorts. To specifically identify the age profile for the COVID-19 variants in 2020 to 2023, we employ the proportion of total deaths at each age which are potentially due to or ‘with’ COVID-19. The original Wuhan strain, and the Alpha variant show somewhat limited divergence in the age profile with the Alpha variant shifted to a moderately higher proportion of deaths below age 84. The Delta variant specifically targeted persons below age 65. The Omicron variants showed significantly lower proportion of overall mortality, with markedly higher relative proportion of deaths above age 65 steeply increasing with age to a maximum around 100 years of age. A similar age profile for the variants can be seen in the age-banded deaths in US states – although slightly obscured by using age bands rather than single year of age. However, the US data shows that higher male deaths are greatly dependent on age and the COVID-variant. Deaths determined as ‘due to’ COVID-19 (as opposed to ‘involving’ COVID-19) in England and Wales were especially over-estimated in 2021 relative to the change in all-cause mortality. This arose as a by-product of an increase in COVID-19 testing capacity in late 2020. Potential structure-function mechanisms for the year of age specificity of SARS-CoV-2 var-iants are discussed. The question is posed as to whether vaccines based on different variants carry the specific age profile through into the vaccine.

show abstract

An integrated strategy to identify COVID‐19 causal genes and characteristics represented by LRRC37A2

Cited by 3 publications

References 88 publications

COVID-19-Related Age Profiles for SARS-CoV-2 Variants in England and Wales and States of the USA (2020 to 2022): Impact on All-Cause Mortality

COVID-19-Related Age Profiles for SARS-CoV-2 Variants in England and Wales and States of the USA (2020 to 2022): Impact on All-Cause Mortality

Integrating population-level and cell-based signatures for drug repositioning

Age Profiles for SARS-CoV-2 Variants in England and Wales and States of the USA (2020 to 2022): Impact on All-Cause Mor-Tality

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