Anavex Life Sciences Corp (AVXL)

[Doc328]

As I have mentioned before, it is irrational for regulators to not approve Blarcamesine – at LEAST for ABCLEAR3, with possible conditions for other subgroups.

I would put zero weight on the ABCLEAR2/3 data. If this is the strategy, the only thing Missling will accomplish is to waste another 4-6 months.

I've gone over this a couple times, The association with COL24A1was determined using GWAS which tests about 1,000,000 variants. Because of multiplicity, p values need to be extremely low,

Despite my near perfect record and detailed referenced posts, people seem to doubt me more than 'experts' who are continuously wrong with their predictions.

Maybe Chatgpt will be trusted more

Please refer to 12x post https://investorshub.advfn.com/boards/read_msg.aspx?message_id=175462381 for the p values (<0.00001) identifying COL24A1 variants and association with cognitive response

GWAS Significance Threshold

In a Genome-Wide Association Study (GWAS), millions of genetic variants are tested at once. Because of the large number of comparisons, a very strict significance threshold is required to avoid false positives.

Standard genome-wide significance threshold:
p < 5 × 10?8

This threshold is roughly equivalent to applying a Bonferroni correction for about one million independent tests (0.05 / 1,000,000 ˜ 5 × 10?8). A variant that meets this threshold is considered strong, reliable evidence of association.

How meaningful is p < 0.00001 (1 × 10?5)?

In GWAS, p < 10?5 is not considered genome-wide significant. It is viewed as a “suggestive” association that requires replication or further study, but it is not reliable on its own.

Interpretation:

p < 5 × 10?8: genome-wide significant (accepted as true association)

5 × 10?8 < p < 1 × 10?5: suggestive; not definitive

p > 1 × 10?5: not meaningful

Because millions of SNPs are tested, values around 10?5 can occur by chance even without a real effect.

and

Would using an identified gene variant at p<0.00001 be hypothesis testing or hypothesis generating

Using a variant identified in a GWAS at p < 0.00001 (1×10?5) is hypothesis-generating, not hypothesis-testing.

Why?

In GWAS, p < 1×10?5 is not genome-wide significant. It is considered a suggestive signal that may or may not represent a true association. Because it does not clear the strict multiple-testing threshold (p < 5×10?8), it cannot be treated as confirmed evidence.

Therefore, a variant at this level:

Suggests a possible biological association

Identifies a direction worth studying

Requires replication in an independent dataset

Cannot be used to formally confirm a hypothesis

This makes it hypothesis-generating.

When does it become hypothesis-testing?

A variant becomes part of hypothesis-testing only when:

It has genome-wide significant evidence (p < 5×10?8), and/or

An independent cohort replicates the association, and/or

It’s being used to test a pre-specified biological hypothesis (not discovered first from GWAS).

Without replication or genome-wide significance, the initial signal remains exploratory.

Summary

p < 1×10?5 in GWAS ? hypothesis-generating

p < 5×10?8 + replication ? hypothesis-testing

If you’d like, I can also give examples or diagrams showing the hierarchy of evidence in GWAS.