AI Uncovers Hidden Genetic Clues That Challenge COVID-19’s Origins

This is really important, but does not answer the important question of just how it happened.  We are talking about two rare human diseases.  Yet surely not rare in a lab.  glanders acts like asian flue and the other as a version of lyme disease.

Both have to also impact domesticaed animal as a matter of course and this surely makes for overlapping infections.  All this gives us a practical path to human infections.  It also gives us a path to lab experiments gone wrong.

I have seen little evidence of a viable public policy response although one is called for.  The best ultimate plan must include localization strategies allowing for diagnostice capture.  that really means enough chickens to support a family and enough cows to support a family all independently.  Again we really know those numbers.

In this manner, an outbreak is contained with minimal impact on the overal market.  it can even be insured against.  Premiums would be catastrophic for larger herds and flocks.

AI Uncovers Hidden Genetic Clues That Challenge COVID-19’s Origins

By KeAi Communications Co., Ltd.

February 11, 2025

https://scitechdaily.com/ai-uncovers-hidden-genetic-clues-that-challenge-covid-19s-origins/

Genetic DNA Sequence

Could COVID-19 have originated from a fusion of rare infectious diseases rather than wildlife? A groundbreaking study using AI-driven max-logistic intelligence suggests exactly that.

A surprising new study suggests that COVID-19 may not have originated from bats or pangolins, but rather from a rare fusion of human diseases.

Using an advanced AI-driven approach called max-logistic intelligence, researchers identified genetic links between COVID-19 and two obscure infections—glanders and Sennetsu fever—potentially rewriting the narrative of how the virus emerged.

Unraveling the Origins of COVID-19

The origins of COVID-19 remain uncertain despite extensive research. A new study published in Advances in Biomarker Sciences and Technology (ABST) takes an AI-driven approach to analyze DNA methylation patterns at 865,859 CpG sites in blood samples from early COVID-19 patients.

Led by Zhengjun Zhang from the University of Wisconsin’s Department of Statistics, the study used max-logistic intelligence to identify strong genetic links. The findings suggest that COVID-19 may have resulted from the natural fusion of two rare infectious diseases — glanders and Sennetsu fever — combined with common human illnesses.

Visualization of Site Site Relationship and Site Risk Probabilities

Visualization of site-site relationship and site-risk probabilities. Credit: Zhang, Z.

A Shift Away from Wildlife Origins

This challenges the widely accepted belief that the virus originated in bats or pangolins, raising the possibility that previous studies placed too much emphasis on wildlife origins.

“Establishing such connections across 865,859 CpG sites is quite a challenge, with random correlations occurring at a probability of less than one in ten million,” says Zhang. “However, when factoring in the rarity of these diseases, the odds of discovering a meaningful link drop to just one in one hundred million, further strengthening the validity of these results.”

Max-Logistic Intelligence: A Game Changer?

Max-logistic intelligence has been previously demonstrated in cancer biomarker studies. Unlike traditional AI algorithms or modern machine learning techniques such as random forests, deep learning, and support vector machines, max-logistic intelligence offers greater interpretability, consistency, and robustness, making it especially useful for establishing causal relationships.

Zhang emphasized that while identifying reliable biomarkers is critical for scientific progress, many gene markers identified in isolated studies fail in other cohorts, resulting in low or no cross-group commonality.

“DNA methylation, the process by which methyl groups are added to DNA, plays a central role in gene expression and disease development,” explains Zhang. “Errors in methylation can trigger diseases, prompting studies into COVID-19’s DNA methylation patterns.”