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Personalisation may improve prostate cancer screening accuracy

Scientists have moved a step closer to genetically personalised prostate cancer screening.
The most common assessment test for the cancer, which mainly affects men over the age of 50, is prostate-specific antigen (PSA) screening which often erroneously indicates signs of the disease.
But a joint team at UC San Francisco and Stanford University, both in the US, have come up with a method they believe will make screening more accurate by calibrating PSA levels to each man’s genetics.
They say applying this type of personalisation could significantly reduce overdiagnosis and better predict aggressive disease. In addition to the regular blood-based PSA test, such customised screening would need a germline genetic test, usually conducted on blood, saliva, or cheek swab samples, to look for inherited genetic variants that affect PSA levels.
Whilst raised PSA levels can be a sign of a cancerous prostate tumour, they can also be caused by other circumstances, like infection, an enlarged prostate, inflammation or simply old age.
In a study published in Nature Medicine, UCSF researchers and their collaborators conducted a large genome-wide association study of PSA in more than 95,000 men without diagnosed prostate cancer. This identified more than 80 novel PSA- associated variants.
They set out to discover whether accounting for genetic factors that cause variations in the levels of PSA that are not attributable to cancer could help improve PSA screening.
Senior author of the study, John Witte, a professor of epidemiology and population health and of biomedical data sciences at Stanford, said: “Some men have higher PSA levels due to their genetics. They don’t have cancer, but the higher PSA level leads to a cascade of unnecessary medical interventions like biopsy.”
Linda Kachuri, a former postdoctoral scholar in the Department of Epidemiology and Biostatistics at UCSF and lead author of the study, added: “PSA levels represent the main diagnostic biomarker for prostate cancer. This test is widely used but not currently implemented as part of a formal screening programme.
“Because of its poor sensitivity and specificity, PSA testing can often lead to detecting latent disease or, in some cases, missing aggressive tumours.”
The researchers identified 128 sites in the genome that can affect a person’s inherent PSA level. They developed a way to calculate PSA that accounts for an individual’s normal genetic variations at these sites – known as a PSA polygenic score, which is a quantitative way of measuring someone’s genetic predisposition for a trait in a single value. In this case, the trait is a higher baseline PSA level.
The researchers leveraged the new data to build a genome-wide polygenic score for PSA.
The polygenic score captured each individual’s genetic predisposition to high PSA levels. The team found the polygenic score was strongly associated with PSA levels in validation cohorts and was not associated with prostate cancer. This confirmed that it reflects benign PSA variation.
To examine whether the polygenic score could improve the detection of clinically significant disease and reduce overdiagnosis, each person’s PSA values were adjusted based on their unique genetic profile.
Dr Kachuri said: “PSA values personalised in this way are more likely to reveal changes in PSA due to prostate cancer because they are corrected for the influence of inherited genetics.”
Applying a correction to PSA levels improved the accuracy of biopsy referral decisions. Roughly 30% of men could have avoided biopsy, though adjusted PSA levels would have missed approximately 9% of positive cell samples.
Most of the latter cancers were low-grade disease that did not require treatment, but the researchers admit the misclassifications point to room for improving the polygenic score.
Dr Kachuri said: “We showed that genetic correction of PSA levels has the potential to both reduce unnecessary biopsies and improve our ability to detect tumours with a more aggressive profile. We hope that our findings represent a step forward in developing informative screening guidelines and reducing the diagnostic grey area in PSA screening.”
While the study was very large, almost 90% of the participants were of predominantly European ancestry.
According to Dr Kachuri, this represents a key limitation because the composition of the study doesn’t fully reflect the patient population impacted by prostate cancer.
The team is now working on a larger study in association with the Million Veteran Program, a US-based national research project launched in 2011 looking at how genes, lifestyle, military experience, and exposures affect health and wellness in former members of the armed forces. More than 950,000 veterans have now joined the MVP.
Nearly 1.5 million new prostate cancer cases are diagnosed each year globally and it is the fifth leading cause of cancer death among men. In the US, one in nine men will be diagnosed with prostate cancer, and one in 40 will die from it.
With a disease as prevalent as prostate cancer the researchers believe even a small improvement in screening could save lives.
Dr Kachuri concluded: “We hope to be able to share findings soon from our efforts to conduct larger and more diverse studies of PSA genetics.”
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AI can predict Alzheimer’s with almost 93% accuracy, researchers say

Alzheimer’s AI can predict the disease with nearly 93 per cent accuracy using more than 800 brain scans, researchers say.
The system identified anatomical changes in the brain linked to the onset of the most common form of dementia, a condition that gradually damages memory and thinking.
The findings build on years of research suggesting AI could help spot early Alzheimer’s risk, predict disease and identify patients whose condition has not yet been diagnosed.
Benjamin Nephew, an assistant research professor at the Worcester Polytechnic Institute in Massachusetts, said: “Early diagnosis of Alzheimer’s disease can be difficult because symptoms can be mistaken for normal ageing.
“We found that machine-learning technologies, however, can analyse large amounts of data from scans to identify subtle changes and accurately predict Alzheimer’s disease and related cognitive states.”
The study used MRI scans, a type of detailed brain imaging, from 344 people aged 69 to 84.
The dataset included 281 scans showing normal mental function, 332 with mild cognitive impairment, an early stage of memory and thinking decline, and 202 with Alzheimer’s.
The scans covered 95 of the brain’s nearly 200 distinct regions and used an AI algorithm to predict patients’ health.
Being able to use AI to help diagnose Alzheimer’s earlier could give patients and doctors crucial time to prepare and potentially slow the progression of the disease.
The analysis showed that one of the top predictive factors was brain volume loss, or shrinkage, in the hippocampus, which helps form memories, the amygdala, which processes fear, and the entorhinal cortex, which helps provide a sense of time.
This pattern held across age and sex, with both men and women aged 69 to 76 showing volume loss in the right part of the hippocampus, suggesting it may be an important area for early diagnosis, the researchers noted.
However, the research also found that the way brain regions shrink differs by sex.
In females, volume loss occurred in the brain’s left middle temporal cortex, which is involved in language and visual perception. In males, it was mainly seen in the right entorhinal cortex
The researchers believe this could be linked to changes in sex hormones, including the loss of oestrogen in women and testosterone in men.
These conclusions could help improve methods of diagnosis and treatment going forward, Nephew said.
More than 7.2m Americans are living with Alzheimer’s, according to the Alzheimer’s Association.
More research is being done to reveal other impacting factors.
Nephew said: “The critical challenge in this research is to build a generalisable machine-learning model that captures the difference between healthy brains and brains from people with mild cognitive impairment or Alzheimer’s disease.”
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